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What are the benefits of random allocation in clinical studies? John Worrall, a philosopher of science, recently questioned whether evidence-based medicine's advice to base therapeutic decisions on the results of randomised controlled trials (RCTs) could be justified. 1 2 Here we provide a response to Worrall and others who challenge the epistemological value of RCTs. Worrall's primary target is the view that RCTs are the only reliable source of evidence for medicine. But in arguing against this strong view, he posits a similarly strong counterposition. Worrall argues that randomisation offers no advantage over balanced systematic designs in which experimental and control groups are carefully matched according to known confounders. The best we can do (as ever) is test our theories against rivals that seem plausible in the light of background knowledge. Once we have eliminated other explanations that we know are possible (by suitable deliberate, or post hoc , control) we have done as much as we can epistemologically. 2

Focusing on this claim, we first discuss Worrall's arguments and then provide reasons to reject this view. There are good reasons to randomise studies of therapeutic interventions; principally, RCTs have the capacity to avoid a form of selection bias that cannot be avoided in observational studies.

Worrall draws the conclusion that randomised trials provide no epistemological benefit from two key arguments:

He criticises the notion promoted in the literature that random allocation controls for known and unknown confounders at baseline. Since the number of unknown (possible) causes are ‘innumerable’, “it would clearly be a miracle if all of those factors just happened to be balanced in the two groups. . . on a single random division.” 2 Indeed, the probability that any single confounder is unevenly distributed in a given RCT ranges from zero to one. 3 Hence, it is possible that some unknown confounder is distributed unevenly between treatment and control and correlated to the effect of intervention that was tested in the RCT.

Randomisation is not essential for controlling selection bias or concealing allocation. Worrall and others 4 maintain that these sources of bias can be equally well eliminated in studies that are not randomised.

Neither ‘1’ nor ‘2’, however, undermines the epistemological benefits of RCTs over observational studies in testing the efficacy of therapeutic interventions. Worrall's first argument is only relevant if the point he makes is not understood (however, ‘1’ is well understood by trial analysts) and ‘2’ suffers from serious problems.

Worrall's ‘1’, while not always explicitly discussed, is nonetheless well recognised in the statistical and epidemiological literature. The crucial point is that it is not necessary that randomisation control for all known and unknown confounders at baseline to make valid statistical inferences. It is not necessary for the purpose of issuing a probability statement to know the value of unmeasured covariates; it is sufficient to know their distribution in probability, which randomisation is designed to provide. 5 Similar knowledge regarding unmeasured covariates is not possible in observational designs. Analysis of observational studies rely on additional assumptions which cannot be easily verified. In short, Worrall's ‘1’ does not undermine standard frequentist statistical tests.

Another epistemological benefit of RCTs over observational studies is the capacity of RCTs to avoid confounding by indication (choice of treatment bias). Confounding by indication, in which treatment assignment is a function of the risk of future health outcomes (prognosis), is a particular problem for observational studies. Even if we match for a number of known factors, it is difficult in observational designs to rule out or account for all the factors which may influence the physicians' treatment assignment or the patients' reasons to accept or decline the intervention (see, for instance, Collins and MacMahon 6 ). RCTs are prone to other biases but not this one.

Eliminating confounding by indication is a strong argument for interventional studies over observational studies. Worrall's ‘2’ claims that it is possible to use alternatives to randomisation to ensure experimental groups are equally balanced for known confounders and conceal allocation. Worrall does not provide details on these alternatives. Presumably, he is focusing on interventional studies and expressing the idea that it is conceptually possible to devise a method (other than randomisation) that stratifies patients according to relevant prognostic information and allocates them to treatment or control that is independent of the investigator. A number of problems can be raised against this suggestion.

First, alternative methods of allocation are not possible for case-control or cohort studies – in these study designs, the patient decides to (or the patient's circumstances lead them to) take or not take the intervention under investigation. Worrall and Borgerson fail to give sufficient weight to the importance of confounding by indication as a justification for interventional studies (and RCTs in particular) over observational studies.

Second, where randomisation is possible and easily carried out, methods that claim to do better than randomisation should be critically examined. Randomising provides a distinct (and uncontroversial) experimental distribution on which to base statistical inferences; this is the case for frequentist 7 8 and Bayesian 9 10 approaches to statistical inference. Alternative methods will require a more complicated statistical model and additional assumptions of the data. This makes the appropriate choice of statistical model and analysis more cumbersome and typically more difficult to defend. These problems vitiate the proposed advantages of a non-random methods of allocation in interventional studies.

It is important to note that none of the previous discussion invalidates the importance of observational studies. RCTs are neither necessary nor sufficient to conclusively establish therapeutic claims: not necessary because alternative methods may be appropriate when the effect size is large relative to bias or random error that may possibly obscure it, 11 and not sufficient because there is more to assessing a therapeutic claim than success in a randomised trial (eg, assessing if the results from a RCT are generalisable). Furthermore, observational studies may be the best available method for particular questions (eg, assessing rare adverse effects of a medication). The question we are addressing here is: do RCTs offer unique epistemological value above and beyond observational studies?

It should be no surprise that a positive result from a well-conducted RCT falls short of providing conclusive proof of the efficacy of an intervention. A number of assumptions need to hold for a causal conclusion to be valid. Different accounts of causation and different approaches to statistical inference spell out the necessary assumptions in different ways. Nancy Cartwright 12 and Dan Steel 13 discuss the assumptions that need to hold on two probabilistic accounts of causation. Senn, 8 with a focus on clinical trials, discusses assumptions within the frequentist approach. The need for these assumptions does not undermine the importance of RCTs for assessing the efficacy of medical interventions.

RCTs offer unique epistemological advantages that cannot be realised via observational studies. Neither does this mean that the observational studies are unimportant nor does this mean that RCTs are the best method for all questions and in all circumstances (as is reflected in the Oxford Centre for Evidence-based Medicine's Levels of Evidence). 14 Rather, (therapeutic) clinical research should be understood as the means to respond to uncertainties about treatment effects of competing interventions, and the design of clinical study (observational vs RCTs) should be matched to the question/uncertainties at hand. 15

Acknowledgments

This article began as a discussion on the Evidence-Based Health email discussion list initiated by BD. The authors would like to acknowledge the members of the EBM discussion group, whose opinion and free sharing of ideas has informed this work.

Competing interests ALC and BD declare no competing interests. SS notes that he is a consultant to the pharmaceutical industry and an academic whose career is furthered by publishing.

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Conducting the Study: Randomization and Allocation

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Study Designs: Basics of Research

Conducting a medical study requires precise planning and effective management. One of the crucial aspects experts must consider, revolves around the participants – the main focus of digital health research. Recruitment procedures, sample size, randomization, and allocation are some of the factors that require careful consideration before the actual start of the study.

Since medical professionals cannot test the whole population due to financial, ethical and time limitations, a representative sample is often needed. At the same time, there’s always a chance that the chosen sample won’t represent the population of interest (Peat, 2011). At the end, when only a portion of the population is studied, there’s always a risk that this particular group does not accurately represent the target population.

Randomization and Allocation

To minimize errors and bias, randomization has become a sufficient way to select participants. Random allocation is another paramount method used to assign participants to different research groups (Peat, 2011). In other words, randomization is a practice that’s used to achieve generalizability, while random allocation – is to minimize confounders and eliminate systematic bias. Thus, random selection and random allocation are the most efficient methods, each with its challenges and advantages.

For instance, random allocation can lead to unbalanced and balanced groups (Peat, 2011). When it comes to unbalanced samples, two methods can be employed: simple randomization (via a random number table or a computer-generated sequence) or quasi-randomization (through a random number; e.g., age). When balanced groups are needed, several methods can be employed. Restricted randomization is one of the effective methods, which is achieved by sealed envelopes. Block randomization, on the other hand, is achieved in small blocks. Another technique is replacement allocation which requires experts to reject sequences when they exceed the pre-specified balance. Dynamically balanced randomization is also vital, and it involves forced allocation to unbalanced groups. Bias coin randomization, which implies that probability is changed in unbalanced groups, can be employed as well. Last but not the least, minimization is a popular method that requires allocation by prognostic factors when there are unbalanced groups

Random Selection and Random Allocation in Details

As explained above, random selection is the most beneficial way to ensure representativeness and generalizability. Random selection can be made from an ordered list. This list can include vital indicators (e.g., towns) which have a unique number. Consequently, these unique numbers can be randomly selected from the list. In studies with less than 100 participants, tables prove to be the most effective way to select subjects. When using a table, the pattern of reading it is important: the table can be read by row, by column or by block (Peat, 2011). After experts have decided on the pattern, a random start should be chosen, and a random sequence should be used to select numbers. Note that any number repeated should be discarded. For studies with more than 100 participants, computer software to generate random number sequences is suggested. Again, since duplicates should be excluded, a longer list is recommended to ensure enough numbers.

Random selection is vital, and so is random allocation. Allocation methods, such as the ones described above, are used to assign participants to two or more study groups (e.g., treatment and control groups). Usually, the allocation is used to remove confounders. Note that experts can control for confounders in the analysis (via post-hoc methods and multivariate data); however, it’s better to do that at the design stage of the study (Peat, 2011). The most effective allocation can be achieved via an unpredictable allocation sequence. To avoid bias, staff should be blinded to the results. Allocation concealment, or when staff does not know what the next intervention allocation will be, is also paramount to diminish selection bias. Balanced groups are the most desired outcome of allocation. Nevertheless, the main aspect to consider is to ensure that each subject has the chance to be allocated to any group and to ensure that differences in groups are due to treatment only. A good practice is to keep the allocation code unavailable until subjects are eligible or until they consent.

Simple Randomization

Another important difference between studies is their qualitative or quantitate nature (Moffatt, 2006). While quantitative methods rely on conventional data collection and statistical procedures, qualitative studies involve open questions and other in-depth methods, such as interviews with patients.

As mentioned above, quantitative studies help researchers collect data and transform it into statistics. Such studies are well structured and can include large samples. As a result, they are widely used in research and medical practice.

On the other hand, qualitative studies can help researchers gain insights and generate testable hypotheses. They can be used parallel to quantitative studies to explore patients’ feelings, attitudes towards a new treatment, and personal tactics to cope with a disease.

Simple randomization is one of the most popular methods used to select and assign subjects (Peat, 2011). It’s also called complete unbalanced or unrestricted randomization. In fact, simple randomization is the best method to perform random allocation. It can be achieved by tossing a coin or by selecting random numbers.

Note that when a random number is taken from a table, experts need to decide how to use it. For example, if a team gets the following numbers:

they can use the following combinations:

On top of that, researchers can use either the first digits of the selected numbers:

or only the last ones:

After the selection of numbers, the subjects are divided into groups.

Simple randomization is a great method that balances prognostic factors. However, it can lead to unbalanced groups. This can become problematic in small studies or across different research centers. Unfortunately, small numbers lack the statistical power to show clinically significant results.

Quasi-randomization

Quasi-randomization is another popular method, which relies on a systematic assignment achieved by essential indicators, such as date of birth or medical number (Kim et al., 2017). Since this method is not exactly random, experts call it quasi-randomization. Note that alternation is another type of quasi-randomization: it’s achieved by following the order via which the subjects were included in the study.

Quasi-randomization may be prone to selection bias and lack of concealment. Another disadvantage of this method is that there’s no balance of confounders or groups.

Block Randomization

Block randomization is a method in which selection and allocation are done by small groups, called blocks (Peat, 2011). This method is beneficial in large studies or multi-centered trials, and also during simple and stratified randomization. Block randomization is used to assure balanced groups. Note that to be effective, blocks must generate all possible combinations.

For example, for a block size of four and two treatment groups (A, B), there are six options:

Blocks should be numbered, after which a number will be selected randomly.

On the other hand, for a group of three for three treatments (A, B, C), the following combinations will be valid:

After forming the blocks, experts need to choose a random order. Let’s look at the following random sequence: 6, 2, 3, 6, 1, etc. In this case, the research team will start with blocks CBA, ACB, and so on and on.

However, the block size can ruin concealment as experts may guess the order at the later stages of research. To minimize bias, the block size can be changed during the study (Peat, 2011).

Another challenge is the need for large blocks. In large blocks, experts may face too many combinations. Note, however, that if there are large blocks but only two treatment groups, random randomization can be used to help experts allocate subjects.

Replacement Randomization

When it comes to selection and allocation, unbalanced groups may distort findings. Thus, replacement randomization is an effective method to guarantee balanced groups. The maximum imbalance should be decided before the study, and new sequences will be continuously generated until the planned criteria are met (Peat, 2011).

However, replacement randomization can become unblinded at the later stages of research. Simply because when the group size increases and the sample decreases, more and more replacements will be needed. For this reason, this method is suitable only in small studies with a few groups, including stratified trials . Yet, replacement randomization guarantees an upper limit of imbalance, and it also provides unpredictable sequences, which is an advantage over other methods, such as block randomization.

Biased Coin Randomization

Biased coin randomization is a popular method which is also known as adaptive randomization.  This technique follows the probability of assigning subjects to different treatment groups to the point when the groups become unbalanced. This means that the probability of assigning subjects to small groups increases to maintain balance (Peat, 2011).

In particular, biased coin randomization can be used when the imbalance between groups exceeds a specific number, which is specified before the study.

Minimization

Minimization is another effective method, which as explained above, is used to ensure a balance of prognostic factors (Peat, 2011). This method is critical for balancing numbers over two and more characteristics. In fact, this is crucial in small studies when differences in confounders can occur just by chance. It’s also vital in large studies – when imbalances may reduce the statistical power of small differences. Note that in minimization, the number of subjects is updated continuously.

It’s interesting to mention that the odds of entry in a group can follow the biased coin method described above; as a result, patients can be allocated to the smaller group. If there’s an equal number, then, simple randomization can be employed.

Dynamic Balanced Randomization

Dynamically balanced randomization is a method that is a variation of replacement randomization (Peat, 2011). In other words, when the pre-specified imbalance has been reached, the next subjects are allocated to the smaller group. This method is beneficial in studies in which randomization by strata is needed. A disadvantage of dynamically balanced randomization, though, is that there’s a risk of ruining concealment. Nevertheless, this research technique is less prone to bias compared to block randomization; also, there’s better protection against imbalance when compared to minimization.

Unequal Randomization

In medical research, equal numbers are the most desired and effective way to achieve meaningful results. Thus, as described above, there are many methods that help experts balance groups during randomization and allocation (Peat, 2011).

However, equal numbers are not always the ultimate solution. For instance, when a new and an old treatment must be compared, more subjects must be randomized in the new treatment group in order to show significant differences (both statistical and clinical differences). In this case, the ratio between new and old treatments can be 2:1 or 3:2. Note that the methods to select and allocate subjects include all the techniques described above (Peat, 2011).

Randomization in Clusters

Last but not the least, epidemiological studies also need some special consideration. When experts need to measure the prevalence of a disease or mortality rates within a community, clusters – not individuals – should be the focus of analysis. For instance, when experts should select children from a particular population, schools must be randomized – not individual students.

However, this method does not account for cultural differences between the chosen communities. There will be a difference between rural and city schools, for example. This can lead to a significant loss of efficiency. However, randomization in clusters can be beneficial in cases when the number of practices is substantial and the number of subjects small. In fact, to reach an adequate sample size, the number of practices and interventions must be considered – not the number of individuals.

Randomization: Conclusion

Randomization and allocation allow experts to exercise control over any clinical trial, eliminate bias, balance groups, and confounders, and give each patient an equal chance of receiving the same treatment (Suresh, 2011). Therefore, randomization is a fundamental part of medical research and sound management practices.

Kim, J., Kim, T., In, J., Lee, D., Lee, S., & Kang, H. (2017). Assessment of risk of bias in quasi-randomized controlled trials and randomized controlled trials reported in the Korean Journal of Anesthesiology between 2010 and 2016. Korean Journal of Anaesthesiology, 70(5), 511-519.

Peat, J. (2011). Conducting the Study. Health Science Research, SAGE Publications, Ltd.

Suresh, K. (2011). An overview of randomization techniques: An unbiased assessment of outcome in clinical research. Journal of Human Reproductive Sciences, 4(1), 8-11.

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What is a Randomized Control Trial (RCT) Study?

Julia Simkus

Research Assistant at Princeton University

Undergraduate at Princeton University

Julia Simkus is a Psychology student at Princeton University. She will graduate in May of 2023 and go on to pursue her doctorate in Clinical Psychology.

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Saul Mcleod, PhD

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Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.

DA randomized control trial (RCT) is a type of study design that involves randomly assigning participants to either an experimental group or a control group .

In This Article

How They Work

In the control group, the participants do not receive the new treatment or intervention but instead receive a placebo or reference treatment.

Apart from the treatment or intervention being studied, the two groups should be supervised and observed identically. Because the participants are randomly assigned , the characteristics between the two groups should be balanced, enabling researchers to attribute any differences in outcome to the study intervention.

Without randomization, researchers might consciously or subconsciously assign patients to a particular group for various reasons.

Since researchers can be confident that any differences between the groups are due solely to the effects of the treatments, scientists view RCTs as the gold standard for clinical trials.

Evidence-based medicine pyramid.

Figure 1 . Evidence-based medicine pyramid. The levels of evidence are appropriately represented by a pyramid as each level, from bottom to top, reflects the quality of research designs (increasing) and quantity (decreasing) of each study design in the body of published literature. For example, randomized control trials are higher quality and more labor intensive to conduct, so there is a lower quantity published.

Prevents bias

In randomized control trials, participants must be randomly assigned to either the intervention group or the control group, such that each individual has an equal chance of being placed in either group.

This is meant to prevent selection bias and allocation bias and achieve control over any confounding variables to provide an accurate comparison of the treatment being studied.

Because the distribution of characteristics of patients that could influence the outcome is randomly assigned between groups, any differences in outcome can be explained only by the treatment.

High statistical power

Because the participants are randomized and the characteristics between the two groups are balanced, researchers can assume that if there are significant differences in the primary outcome between the two groups, the differences are likely to be due to the intervention.

This warrants researchers to be confident that randomized control trials will have high statistical power compared to other types of study designs.

Since the focus of conducting a randomized control trial is eliminating bias, blinded RCTs can help minimize any unconscious information bias.

In a blinded RCT, the participants do not know which group they are assigned to or which intervention is received. This blinding procedure should also apply to researchers, health care professionals, assessors, and investigators when possible.

“Single-blind” refers to an RCT where participants do not know the details of the treatment, but the researchers do.

“ Double-blind ” refers to an RCT where both participants and data collectors are masked of the assigned treatment.

Limitations

Costly and timely.

Some interventions require years or even decades to evaluate, rendering them expensive and time-consuming.

It might take an extended period of time before researchers can identify a drug’s effects or discover significant results.

Requires large sample size

There must be enough participants in each group of a randomized control trial so researchers can detect any true differences or effects in outcomes between the groups.

Researchers cannot detect clinically important results if the sample size is too small.

Change in population over time

Because randomized control trials are longitudinal in nature, it is almost inevitable that some participants will not complete the study, whether due to death, migration, non-compliance, or loss of interest in the study.

This tendency is known as selective attrition and can threaten the statistical power of an experiment.

Randomized control trials are not always practical or ethical, and such limitations can prevent researchers from conducting their studies.

For example, a treatment could be too invasive, or administering a placebo instead of an actual drug during a trial for treating a serious illness could deny a participant’s normal course of treatment. Without ethical approval, a randomized control trial cannot proceed.

Fictitious Example

An example of an RCT would be a clinical trial comparing a drug’s effect or a new treatment on a select population.

The researchers would randomly assign participants to either the experimental group or the control group and compare the differences in outcomes between those who receive the drug or treatment and those who do not.

Real-life Examples

How to reference this article:

Simkus, J. (2022, March 03). Randomized Controlled Trial . Simply Psychology. simplypsychology.org/randomized-controlled-trial.html

Further Information

Cocks, K., & Torgerson, D. J. (2013). Sample size calculations for pilot randomized trials: a confidence interval approach. Journal of clinical epidemiology, 66(2), 197-201.

Kendall, J. (2003). Designing a research project: randomised controlled trials and their principles. Emergency medicine journal: EMJ, 20(2), 164.

Akobeng, A.K., Understanding randomized controlled trials. Archives of Disease in Childhood , 2005; 90: 840-844.

Bell, C. C., Gibbons, R., & McKay, M. M. (2008). Building protective factors to offset sexually risky behaviors among black youths: a randomized control trial. Journal of the National Medical Association, 100 (8), 936-944.

Bhide, A., Shah, P. S., & Acharya, G. (2018). A simplified guide to randomized controlled trials. Acta obstetricia et gynecologica Scandinavica, 97 (4), 380-387.

Botvin, G. J., Griffin, K. W., Diaz, T., Scheier, L. M., Williams, C., & Epstein, J. A. (2000). Preventing illicit drug use in adolescents: Long-term follow-up data from a randomized control trial of a school population. Addictive Behaviors, 25 (5), 769-774.

Demetroulis, C., Saridogan, E., Kunde, D., & Naftalin, A. A. (2001). A prospective randomized control trial comparing medical and surgical treatment for early pregnancy failure. Human Reproduction, 16 (2), 365-369.

Gillis, C., Li, C., Lee, L., Awasthi, R., Augustin, B., Gamsa, A., … & Carli, F. (2014). Prehabilitation versus rehabilitation: a randomized control trial in patients undergoing colorectal resection for cancer. Anesthesiology, 121 (5), 937-947.

Globas, C., Becker, C., Cerny, J., Lam, J. M., Lindemann, U., Forrester, L. W., … & Luft, A. R. (2012). Chronic stroke survivors benefit from high-intensity aerobic treadmill exercise: a randomized control trial. Neurorehabilitation and Neural Repair, 26 (1), 85-95.

Guyatt, G. (1991). A randomized control trial of right-heart catheterization in critically ill patients. Journal of Intensive Care Medicine, 6 (2), 91-95.

MediLexicon International. (n.d.). Randomized controlled trials: Overview, benefits, and limitations. Medical News Today. Retrieved from https://www.medicalnewstoday.com/articles/280574#what-is-a-randomized-controlled-trial

Wilson, B. A., Emslie, H., Quirk, K., Evans, J., & Watson, P. (2005). A randomized control trial to evaluate a paging system for people with traumatic brain injury. Brain Injury, 19 (11), 891-894.

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What random assignment does and does not do

Affiliation.

Random assignment of patients to comparison groups stochastically tends, with increasing sample size or number of experiment replications, to minimize the confounding of treatment outcome differences by the effects of differences among these groups in unknown/unmeasured patient characteristics. To what degree such confounding is actually avoided we cannot know unless we have validly measured these patient variables, but completely avoiding it is quite unlikely. Even if this confounding were completely avoided, confounding by unmeasured Patient Variable x Treatment Variable interactions remains a possibility. And the causal power of the confounding variables is no less important for internal validity than the degree of confounding.

Copyright 2003 Wiley Periodicals, Inc. J Clin Psychol.

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Control: Random Allocation and Counterbalancing, Randomisation and Standardisation

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The difference between allocation concealment and blinding in randomised controlled trials

what does random allocation control for

Allocation concealment and blinding are characteristics that prevent bias in randomised controlled trials and experimental studies. However, these concepts are often confused. Using a randomised controlled trial as an example, the statistician Philip Sedgwick explains the differences between allocation concealment and blinding, and why these characteristics are important:

Researchers investigated whether a nutritious meal and food packages was more effective at encouraging completion of tuberculosis treatment compared to nutritional advice alone. Participants were 270 adults with untreated and newly diagnosed tuberculosis recruited from primary care clinics in Dili, Timor-Leste. Participants were randomised to treatment or control group using a computer-generated randomisation sequence. Participants were allocated to either group with the randomisation sequence concealled in sequentially numbered, opaque sealed envelopes. An outcome assessor blinded to participants’ allocated group assessed the primary outcome.

In a clinical trial, random allocation is needed so that participants in treatment and control groups are similar at baseline. This allows us to conclude whether results observed are due to differences in treatment, rather than differences in baseline characteristics between groups. Consequently, random allocation of participants to treatment or control groups is needed to infer causal effects of the treatment on outcomes.

Allocation concealment means participants and investigators (eg. investigators who provide the treatment, assess the outcome, or analyse the data) are not aware of the allocation sequence before random allocation occurs. That is, before randomisation, neither participants nor investigators know which group a participant will be allocated to. Blinding means (some) participants and investigators are not aware of which group a participant is allocated to after random allocation occurs.

Allocation concealment is needed to prevent the random allocation sequence from being undermined during recruitment and treatment allocation. If participants and investigators know the allocation sequence before random allocation occurs, investigators may select (unconsciously or otherwise) which participants are recruited, or the order in which participants are recruited. For example, investigators might think some participants would not accept or would be unsuitable for the next allocated group in the sequence. Without allocation concealment, participants might also “self-select” or choose to particpate or not participate based on whether they favour or dislike the next allocated group in the sequence. Staying faithful to the randomised sequence can be difficult. Indeed, the physician Kenneth Schulz writes about the lengths some investigators go to in order to break the allocation concealment.

Allocation concealment prevents selection bias, or a systematic difference between participants who are recruited for a trial and those who are not. This results in a sample that does not represent the population. Allocation concealment also prevents allocation bias, that is, a systematic difference between participants in how they are allocated to treatment or control groups.

Allocation concealment is always possible in clinical trials and is needed to achieve blinding, but blinding is not always possible. In the example above, allocation concealment was achieved by concealing the allocation sequence in opaque sealed envelopes. However, participants and investigators providing the treatment (nutritious meal or nutritional advice) could not be blind to allocated group. This means it was still possible for participants to demonstrate a response bias without blinding. However, the outcome was assessed by an investigator blind to group, which would help minimise assessor bias.

Allocation concealment and blinding prevent different types of biases in randomised controlled trials and other studies. Allocation concealment is always possible in clinical trials but blinding is not always possible. Readers need to be cognizant of whether and how these biases were prevented in order to judge the credibility of research findings.

Schulz KF and Grimes DA (2002) Allocation concealment in randomised trials: defending against deciphering. Lancet 359:614-618.

Sedgwick P (2013) Allocation concealment vs blinding in randomised controlled trials BMJ 347:f5518.

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Allocation concealment in randomised controlled trials: are we getting better?

Laura Clark and colleagues assess the allocation concealment methods in a sample of randomised controlled trial publications

A robust randomised controlled trial (RCT) must use allocation concealment—that is, separate the act of randomisation from the person recruiting participants. Poor randomisation methods cause exaggerated treatment effects, are open to subversion by researchers or clinicians, and have a knock-on effect on systematic reviews. 1 2 3

The CONSORT statement, which leading medical journals endorse, states that the method of allocation (comprising sequence generation, allocation concealment mechanism, and implementation) should be clearly described. 4 Allocation concealment is dependent on the method of sequence generation as well as the concealment mechanism.

Almost a fifth of trials published in major medical journals in 2002 used inadequate concealment, and a quarter failed to describe how the allocation was concealed. 2 Here we examine a sample of RCTs published in 2015 to see whether the situation has improved.

Defining inadequate allocation concealment

We searched four high impact medical journals ( The BMJ, Journal of the American Medical Association (JAMA); the Lancet , and the New England Journal of Medicine (NEJM)) and found 79 RCTs published between June and August 2015. We extracted and judged their mechanism for allocation concealment, taking into consideration the study design, sequence generation method, and allocation concealment mechanism. We defined an inadequate process as one that used envelopes as the method of allocation concealment (box 1) or used stratified block randomisation by site with small block sizes as the sequence generation method (box 2), except in double blind trials. If insufficient detail was provided in the paper, we checked the protocol or emailed the authors.

Box 1: Sequentially numbered opaque sealed envelopes (SNOSE)

Envelopes containing the treatment allocation are opened by the recruiting clinician on participant enrolment. To be robust, the envelopes should be truly opaque, sequentially numbered, and opened in the correct order. The clinician …

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what does random allocation control for

what does random allocation control for

How to Do Random Allocation (Randomization)

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what does random allocation control for

what does random allocation control for

Randomized controlled trials (RCT) are known as the best method to prove causality in spite of various limitations. Random allocation is a technique that chooses individuals for treatment groups and control groups entirely by chance with no regard to the will of researchers or patients' condition and preference. This allows researchers to control all known and unknown factors that may affect results in treatment groups and control groups.

Allocation concealment is a technique used to prevent selection bias by concealing the allocation sequence from those assigning participants to intervention groups, until the moment of assignment. Allocation concealment prevents researchers from influencing which participants are assigned to a given intervention group. This process must be included in the experiment for the success of any RCT.

Blinding refers to keeping trial participants, health care providers, assessors or data collectors unaware of the assigned intervention, so that they will not be influenced by that knowledge. This process is conducted to minimize possible bias in implementation, dropouts, measurements, etc. Blinding is not always feasible for RCT but should be implemented if possible.

Randomization, allocation concealment and blinding should be well implemented and should be described in the paper.

On the other hand, many researchers are still unfamiliar with how to do randomization, and it has been shown that there are problems in many studies with the accurate performance of the randomization and that some studies are reporting incorrect results. So, we will introduce the recommended way of using statistical methods for a randomized controlled study and show how to report the results properly.

Simple Randomization

The easiest method is simple randomization. If you assign subjects into two groups A and B, you assign subjects to each group purely randomly for every assignment. Even though this is the most basic way, if the total number of samples is small, sample numbers are likely to be assigned unequally. For this reason, we recommend you to use this method when the total number of samples is more than 100.

Block Randomization

We can create a block to assign sample numbers equally to each group and assign the block.

If we specify two in one block (the so-called block size is two), we can make two possible sequences of AB and BA. When we randomize them, the same sample numbers can be assigned to each group. If the block size is four, we can make six possible sequences; these are AABB, ABAB, ABBA, BAAB, BABA, BBAA, and we randomize them.

However, there is a disadvantage in that the executer can predict the next assignment. We can easily know the fact that B comes after A if the block size is two and if the block size is four; we can predict what every 4th sample is. This is discordant with the principle of randomization. To solve this problem, the allocator must hide the block size from the executer and use randomly mixed block sizes. For example, the block size can be two, four, and six.

Stratified Randomization

Randomization is important because it is almost the only way to assign all the other variables equally except for the factor (A and B) in which we are interested. However, some very important confounding variables can often be assigned unequally to the two groups. This possibility increases when the number of samples is smaller, and we can stratify the variables and assign the two groups equally in this case.

For example, if the smoking status is very important, what will you do? First, we have two methods of randomization that we learned previously. There are two randomly assigned separate sequences for smokers and non-smokers. Smokers are assigned to the smoker's sequences, and non-smokers are assigned to the non-smoker's sequences. Therefore, both smokers and non-smokers groups will be placed equally with the same numbers.

So we can use 'simple randomization with/without stratification' or 'block randomization with/without stratification.' However, if there are multiple stratified variables, it is difficult to place samples in both groups equally with the same numbers. Usually two or fewer stratified variables are recommended.

Although there are websites or common programs for randomization, let us use an Excel file. Download the attached file in http://cafe.naver.com/easy2know/6427 . It is in a 'Read-only' state, but there is no limit in function; it is in the 'Read-only' state only to prevent accidental modification.

Random Allocation

An independent researcher makes random allocation cards using computer-generated random numbers. He keeps the original random allocation sequences in an inaccessible third place and works with a copy. Since the executers can get confused with the original coding of A and B later, the allocator should record exactly what these codes mean to avoid further confusion.

Here in Fig. 6 , '^m' is a special character for manual page break. After setting it as shown, you click 'all change' and print it out. Then we can get it printed per sheet. The inside of the envelope should not be visible from the outside, and it has to be printed out for each one and put in an envelope after being folded several times. In some papers, even aluminum foil was used to hide the print to prevent it from being read with a flash of light.

There are serial numbers on the outside of the envelopes. Input date, time, patient ID, results after the procedure, etc. usually will be recorded on the envelope or another sheet inside of the envelope, also.

Drug Preparation

An independent nurse (researcher) prepares syringes with "drug A" and "drug B" and puts them into envelopes according to the allocation orders. These syringes cannot be distinguished because they contain the same colored liquid with the same volume. Or pills or tablets with the same color and shape (placebo) will be put into the envelopes according to the allocation orders.

In the case of surgical treatment, an independent researcher prepares the envelopes, including writing the treatment name on a sheet of paper inside it. In the operation room, another independent nurse (researcher) opens the envelope and informs the doctor to do the treatment that is written on the paper in the envelope.

Another independent nurse injects the drug or the doctor performs the operation according to the order. The patient's ID, date, time and other information are recorded on each envelope. The nurse and the patient would not know what drugs are injected (double blinded). The doctor knows the treatment and the patient does not know it (one blinded). The preparer retrieves the envelopes and checks to see if the operation (and injection) was done as planned.

In the case of broken or lost syringes, the preparer figures out what the number of the envelope it is and replaces the envelope with the same drug according to the allocation.

The envelopes should be opened just before the injection or operation. For example, when a patient comes, an envelope is opened; however, if this does not meet the criteria for the performance of the study, this can be cancelled. Also, if the operator finds out before an operation the tool that is to be inserted, it is impossible to get the operation as planned. For example, even though plate A was assigned to be used, if the patient was indicated to have some other surgery because of infection or severe osteoporosis, you will waste an envelope and it will cause confusion as well as violate the randomization. All these cases should be mentioned as inclusion criteria and exclusion criteria in advance. To avoid this, the envelopes should be opened just before the operation or injection if possible.

However, in cases where the operation tool is so big that two tools cannot be prepared at the same time, or the preparation takes a lot of money (robotic surgery, etc.) or time (liver transplantation, etc.), the envelopes can be opened in advance.

Also, although you open an envelope and choose the procedure that you see, other conditions that affect the outcome can occur. For example, the patient could be admitted to the intensive care unit for medical problems after treatment, or may not get enough rehabilitation treatment for some other reasons.

In this case, it is an important issue whether to consider this as a follow-up loss or exclude this case from the study. We can deal with this issue by focusing on intention-to-treat analysis and per-protocol analysis. We will study this later when we get a chance.

Survey Results

After a period of time, another independent researcher measures the patient's outcome. He does not know the allocation. That is another blinding, so triple blinding is recommended if possible.

Another independent researcher who was not involved in any stage of these procedures will do the statistical analysis (sometimes a statistician). He even does not know the treatment name because the treatment name is hidden, as in A and B.

From 1988 to 2000, 72 of 2,468 papers (2.9%) in the Journal of Born and Joint Surgery were RCTs. 1) It has been suggested that in some of the papers, randomization was not completely done or the result was not properly reported. According to the analysis of RCTs using painkillers from the January issue in 1966 to the June issue in 2006, 23.9% of the papers were inadequate in terms of the randomization. 2) It would be helpful to see a CONSORT checklist and examples. The following were used in the actual papers and extracted from examples in the CONSORT ( http://www.consort- statement.org ).

Sequence Generation

"Independent pharmacists dispensed either active or placebo inhalers according to a computer generated randomization list."

"For allocation of the participants, a computer-generated list of random numbers was used."

Type of Randomization

"Randomization sequence was created using Stata 9.0 (StataCorp, College Station, TX, USA) statistical software and was stratified by center with a 1:1 allocation using random block sizes of 2, 4, and 6."

"Participants were randomly assigned following simple randomization procedures (computerized random numbers) to 1 of 2 treatment groups."

We can apply the above examples to our case as follows: Randomization sequence was created using Excel 2007 (Microsoft, Redmond, WA, USA) with a 1:1 allocation using random block sizes of 2 and 4 by an independent doctor. In this way, sequence generation and type of randomization can be expressed at the same time.

Allocation Concealment Mechanism

"The doxycycline and placebo were in capsule form and identical in appearance. They were pre-packed in bottles and consecutively numbered for each woman according to the randomization schedule. Each woman was assigned an order number and received the capsules in the corresponding pre-packed bottle."

"The allocation sequence was concealed from the researcher (JR) enrolling and assessing participants in sequentially numbered, opaque, sealed and stapled envelopes. Aluminum foil inside the envelope was used to render the envelope impermeable to intense light. To prevent subversion of the allocation sequence, the name and date of birth of the participant was written on the envelope and a video tape made of the sealed envelope with participant details visible. Carbon paper inside the envelope transferred the information onto the allocation card inside the envelope and a second researcher (CC) later viewed video tapes to ensure envelopes were still sealed when participants' names were written on them. Corresponding envelopes were opened only after the enrolled participants completed all baseline assessments and it was time to allocate the intervention."

The second example was described in great detail, and we can guess how important the randomization and concealment were.

Who Generated the Allocation Sequence, Who Enrolled Participants, and Who Assigned Participants to Interventions?

"Determination of whether a patient would be treated by streptomycin and bed-rest (S case) or by bed-rest alone (C case) was made by reference to a statistical series based on random sampling numbers drawn up for each sex at each center by Professor Bradford Hill (this means that the stratification was done by sex and center); the details of the series were unknown to any of the investigators or to the coordinator. After acceptance of a patient by the panel, and before admission to the streptomycin center, the appropriate numbered envelope was opened at the central office; the card inside told, if the patient was to be an S or a C case, and this information was then given to the medical officer of the center."

"Details of the allocated group were given on colored cards contained in sequentially numbered, opaque, sealed envelopes. These were prepared at the NPEU and kept in an agreed location on each ward. Randomization took place at the end of the 2nd stage of labor when the midwife considered a vaginal birth was imminent. To enter a woman into the study, the midwife opened the next consecutively numbered envelope."

"Block randomization was by a computer generated random number list prepared by an investigator with no clinical involvement in the trial. We stratified by admission for an oncology related procedure. After the research nurse had obtained the patient's consent, she telephoned a contact who was independent of the recruitment process for allocation consignment."

If Done, Who Was Blinded after Assignment to Interventions and How

"Whereas patients and physicians allocated to the intervention group were aware of the allocated arm, outcome assessors and data analysts were kept blinded to the allocation."

"Blinding and equipoise were strictly maintained by emphasizing to intervention staff and participants that each diet adheres to healthy principles, and each of them is advocated by certain experts to be superior for long-term weight-loss. Except for the interventionists (dieticians and behavioral psychologists), investigators and staff were kept blind to diet assignment of the participants. The trial adhered to established procedures to maintain separation between staff that take outcome measurements and staff that deliver the intervention. Staffs who obtained outcome measurements were not informed of the diet group assignment. Intervention staffs, dieticians and behavioral psychologists who delivered the intervention did not take outcome measurements. All investigators, staffs, and participants were kept masked to outcome measurements and trial results."

In short, in a paper, we have to report who was kept blinded. In the case of physical therapy or surgery, keeping the surgeon blinded would be difficult or even impossible; however, blinding is possible for the person who measures the outcome. Anyhow, all individuals who were kept blinded must be described in the report.

To help with all the procedures of a fully qualified RCT, the following systems including electronic case report forms (eCRFs) are available for researchers.

iCReaT (clinical research and trial management system) in Korea Centers for Disease Control & Prevention (KCDC; http://icreat.nih.go.kr ): free for pre-educated and qualified researchers; there are regular education programs once a month, and some hospitals (for example, Severance Hospital) have their own educational programs. An English version will be available soon for non-Korean researchers.

MRCC ( https://mrcc.snuh.org ): for Seoul National University Hospital only. It is relatively inexpensive and includes statistical counseling.

Velos ( http://eresearch.ncc.re.kr ): a world-famous system and very expensive; it is available at National Cancer Center in Korea ( http://ncc.re.kr/crcc/ ).

In RCT, random assignment is important and performing it is easy if you know how to do it. Besides the practice of randomization, correct reporting of the randomization process is also important and it should be done very accurately.

No potential conflict of interest relevant to this article was reported.

what does random allocation control for

Allocation concealment: the key to effective randomisation

Posted on 26th August 2016 by Ed Walsh

what does random allocation control for

Randomisation and allocation concealment

Randomisation – the process of assigning participants to groups so that each participant has an equal chance of being assigned to a given group – is often used in medical research. It ensures different groups being studied have similar characteristics when the study begins, allowing a fair comparison. However proper randomisation is not easy to achieve.

For randomisation to work, trial designers need to come up with an unpredictable randomisation sequence. Unfortunately, trial investigators sometimes work out the sequence, allowing them to influence who ends up in which group. Not so random randomisation.

This is where allocation concealment comes in. Proper allocation concealment keeps trial investigators and participants unaware of upcoming allocations. This can be hard to get your head around to start with. Let’s look at two examples and see what happens first without, and then with, allocation concealment.

Research without allocation concealment

allocation

Matt is designing a trial to see whether his new drug, pretendacetamol, is more effective than a placebo at reducing pain. Matt comes up with an unpredictable randomisation sequence using a random number generator. So far so good.

He posts his carefully planned sequence on a bulletin board, allowing everyone involved in the trial to see the upcoming allocations. The lack of allocation concealment allows the trial investigators – intentionally or unintentionally – to direct participants towards which group they believe is most suitable.

The trial investigators select participants with a better potential for pain relief for the pretendacetamol group. This introduces selection bias and makes pretendacetamol seem far more effective than it actually is. Nightmare.

Allocation concealment done properly

Jack is also doing a trial for his new pain killing drug, imaginaryprofun. He makes an unpredictable randomisation sequence just like Matt did.

Jack tells the trial investigators to ring a number when a new participant has given their consent to enter into the study. When the number is called, an automated system takes the details of the new participant and assigns them to a group, as per Jack’s randomisation sequence.

Since the trial investigators have no way of knowing which participant will go in which group, they have no influence on the randomisation. The results give a fair representation of imaginaryprofun.

Randomisation done right

Hopefully the examples above make it clear that not all randomisation is equal. Both Matt and Jack technically designed a randomised controlled trial, but one randomisation process was far better than the other. This is why it’s so important to look through the methodology before passing judgement on research.

But Matt is just an example to illustrate the point, right? Wouldn’t important research make sure adequate allocation concealment took place? Well, in short, the answer is no.

In a review in the BMJ, it was found that over 40% of trials published in major medical journals either used inadequate allocation concealment or failed to describe how they concealed allocation.

That is a huge number of studies in the most reputable journals presenting results potentially skewed by poor allocation concealment.

So be wary! The devil’s in the detail.

If you have any questions about allocation concealment please don’t hesitate to leave a comment or get in touch.

Hewitt, C., Hahn, S., Torgerson, D., Watson, J. and Bland, J. (2005) ‘ Adequacy and reporting of allocation concealment: review of recent trials published in four general medical journals ‘, BMJ , [online] 330(7499), pp.1057-1058.

Schulz, K. (2000) ‘ Assessing allocation concealment and blinding in randomised controlled trials: why bother ?’, Evidence-Based Mental Health , 3(1), pp.4-5.

Schulz, K. and Grimes, D. (2002) ‘ Allocation concealment in randomised trials: defending against deciphering ‘, The Lancet , 359(9306), pp.614-618.

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Thanks for this great explanation. Was looking all over for a simple explanation.

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“it ensures different groups being studied have similar characteristics when the study begins, allowing a fair comparison”

Does it? You can have strongly unmabalanced characteristics despite randomisation. To my knowledge, randomisation is needed to avoid selection bias.

Anyway, thanx for this post!

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Sorry for the late reply! You are correct in that randomisation is needed to avoid selection bias.

In large trials random allocation should ensure balance in patient characteristics. With smaller trials this is not always the case, which is where minimisation comes in.

If you’re interested I recommend an article by Altman and Bland in the BMJ titled ‘Treatment allocation by minimisation’. You can access it with this link:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC556084/

Thanks for reading!

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Dear Ed Thanks. This is a very well written illustration of an important but widely unappreciated issue. We will add it to the Critical thinking and Appraisal Resource Library (CARL) at http://www.testingtreatments.org . Iain C

Thanks very much, I’m glad you liked it.

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Research Control

Last updated 22 Mar 2021

There are several ways in which research can be controlled to eliminate extraneous variables.

Random allocation of participants is an extremely important process in research. In order to assess the effect of one variable on another, all variables other than the variable to be investigated need to be controlled. Random allocation greatly decreases systematic error, so individual differences in responses or ability are far less likely to consistently affect results.

Counterbalancing is a method used to deal with extraneous effects caused by order effects that arise when using a repeated measures design. The sample is split in half with one half completing the two conditions in one order and the other half completing the conditions in the reverse order. Eg, the first 10 participants would complete condition A followed by condition B but the remaining 10 participants would complete condition B then A. Any order effects should be balanced out by the opposing half of participants.

Randomisation is used in the presentation of trials to avoid any systematic errors that the order of the trials might present.

Standardisation refers to the process in which procedures used in research are kept the same. Great attention is taken to keep all elements of a procedure identical, so that methods are sensitive to any change in performance. Under these circumstances changes in data can be attributed to the I.V. In addition, it is far more likely that results will be replicated on subsequent occasions when research is standardised, which means that data reflects a meaningful pattern and was not a one-off chance result.

Demand characteristics occur when a participant tries to make sense of the research situation, and as a result changes their behaviour. This distorts results, as a participants might intentionally try to demonstrate what the researcher is investigating, or display the opposite (the screw you effect). Participants sometimes try to present themselves in a positive light rather than producing genuine responses/ behaviours, this is known as social desirability bias.

Investigator Effects occur when the presence of the investigator themselves affects the outcome of the research. Eg. during an interview the participants might feel self-conscious or might be influenced by behavioural cues from the researcher (nodding, smiling, frowning etc.).

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The Definition of Random Assignment According to Psychology

Kendra Cherry, MS, is the author of the " Everything Psychology Book (2nd Edition) " and has written thousands of articles on diverse psychology topics. Kendra holds a Master of Science degree in education from Boise State University with a primary research interest in educational psychology and a Bachelor of Science in psychology from Idaho State University with additional coursework in substance use and case management.

what does random allocation control for

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

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Random assignment refers to the use of chance procedures in psychology experiments to ensure that each participant has the same opportunity to be assigned to any given group. Study participants are randomly assigned to different groups, such as the experimental group or treatment group.

Random assignment might involve tactics such as flipping a coin, drawing names out of a hat, rolling dice, or assigning random numbers to participants.

It is important to note that random assignment differs from random selection . While random selection refers to how participants are randomly chosen to represent the larger population, random assignment refers to how those chosen participants are then assigned to experimental groups.  

Random Assignment In Research

To determine if changes in one variable lead to changes in another variable, psychologists must perform an experiment. Researchers often begin by forming a testable hypothesis predicting that one variable of interest will have some impact on another variable.

The variable that the experimenters will manipulate in the experiment is known as the independent variable , while the variable that they will then measure is known as the dependent variable. While there are different ways to look at relationships between variables, an experiment is the best way to get a clear idea if there is a cause-and-effect relationship between two or more variables.

Once researchers have formulated a hypothesis, conducted background research, and chosen an experimental design, it is time to find participants for their experiment. How exactly do researchers decide who will be part of an experiment? As mentioned previously, this is often accomplished through something known as random selection.

Random Selection

In order to generalize the results of an experiment to a larger group, it is important to choose a sample that is representative of the qualities found in that population. For example, if the total population is 51% female and 49% male, then the sample should reflect those same percentages.

Choosing a representative sample is often accomplished by randomly picking people from the population to be participants in a study. Random selection means that everyone in the group stands an equal chance of being chosen.   Once a pool of participants has been selected, it is time to assign them into groups.

By randomly assigning the participants into groups, the experimenters can be fairly sure that each group will be the same before the independent variable is applied.

Participants might be randomly assigned to the control group , which does not receive the treatment in question. Or they might be randomly assigned to the experimental group , which does receive the treatment.

Random assignment increases the likelihood that the two groups are the same at the outset. That way any changes that result from the application of the independent variable can be assumed to be the result of the treatment of interest.  

Example of Random Assignment

Imagine that a researcher is interested in learning whether or not drinking caffeinated beverages prior to an exam will improve test performance. After randomly selecting a pool of participants, each person is randomly assigned to either the control group or the experimental group.

The participants in the control group consume a placebo drink prior to the exam that does not contain any caffeine. Those in the experimental group, on the other hand, consume a caffeinated beverage before taking the test.

Participants in both groups then take the test, and the researcher compares the results to determine if the caffeinated beverage had any impact on test performance.

A Word From Verywell

Random assignment plays an important role in the psychology research process. Not only does this process help eliminate possible sources of bias,   but it also makes it easier to generalize the results of a tested sample population to a larger population.

Random assignment helps ensure that members of each group in the experiment are the same, which means that the groups are also likely more representative of what is present in the larger population. Through the use of this technique, psychology researchers are able to study complex phenomena and contribute to our understanding of the human mind and behavior.

Sullivan L. Random assignment versus random selection . In: The SAGE Glossary of the Social and Behavioral Sciences. Thousand Oaks: SAGE Publications, Inc.; 2009. doi:10.4135/9781412972024.n2108

Lin Y, Zhu M, Su Z. The pursuit of balance: An overview of covariate-adaptive randomization techniques in clinical trials . Contemp Clin Trials. 2015;45(Pt A):21-25. doi:10.1016/j.cct.2015.07.011

Alferes VR. Methods of Randomization in Experimental Design. Los Angeles: SAGE; 2012.

Nestor PG, Schutt RK. Research Methods in Psychology: Investigating Human Behavior. Los Angeles: SAGE; 2015.

By Kendra Cherry Kendra Cherry, MS, is the author of the "Everything Psychology Book (2nd Edition)" and has written thousands of articles on diverse psychology topics. Kendra holds a Master of Science degree in education from Boise State University with a primary research interest in educational psychology and a Bachelor of Science in psychology from Idaho State University with additional coursework in substance use and case management.

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Allocation Concealment

Allocation Concealment is a technique used to prevent selection bias in Randomised Controlled Trials (RCT’s) by concealing the allocation sequence from those assigning participants to the intervention groups, until the moment of assignment. Thus it prevents researchers from (unconsciously or otherwise) influencing which participants are assigned to the intervention or control group.

The UK Medical Research Council’s famous trial of streptomycin treatment for pulmonary tuberculosis is regarded as the first properly conducted randomised clinical trial. The two steps described for allocation concealment were

…random sampling numbers [were] drawn up for each sex at each centre by Professor Bradford Hill. (Allocation sequence generation) … the details of the series … were contained in a set of sealed envelopes, each bearing on the outside only the name of the hospital and a number. (Allocation sequence concealment)

Thus, Randomisation in practice depends on two important aspects:

Proper allocation concealment prevents knowledge of future assignments. On average, trials with inadequate allocation concealment exaggerated estimated treatment effects, i.e. odds ratios, by 41 %. Inadequate allocation concealment is a leading cause of bias in clinical trials.

Generation of allocation sequences

Concealment of allocation sequences

Allocation concealment is often confused with blinding. Allocation concealment attempts to prevent selection and confounding biases and can always be implemented while blinding reduces measurement bias.

Besides the above, it is also important to know who generated the allocation sequence, who enrolled participants and who assigned them to trial groups, as at each of these stages bias could be introduced.

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Learn More:

Schulz, K. F. (2000). Assessing allocation concealment and blinding in randomised controlled trials: why bother?. Evidence Based Mental Health , 3 (1), 4-5.

Paludan-Müller, A., Laursen, D. R. T., & Hróbjartsson, A. (2016). Mechanisms and direction of allocation bias in randomised clinical trials. BMC Medical Research Methodology , 16 (1), 133.

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How to Do Random Allocation (Randomization)

Jeehyoung kim.

Department of Orthopedic Surgery, Seoul Sacred Heart General Hospital, Seoul, Korea.

Wonshik Shin

To explain the concept and procedure of random allocation as used in a randomized controlled study.

We explain the general concept of random allocation and demonstrate how to perform the procedure easily and how to report it in a paper.

Randomized controlled trials (RCT) are known as the best method to prove causality in spite of various limitations. Random allocation is a technique that chooses individuals for treatment groups and control groups entirely by chance with no regard to the will of researchers or patients' condition and preference. This allows researchers to control all known and unknown factors that may affect results in treatment groups and control groups.

Allocation concealment is a technique used to prevent selection bias by concealing the allocation sequence from those assigning participants to intervention groups, until the moment of assignment. Allocation concealment prevents researchers from influencing which participants are assigned to a given intervention group. This process must be included in the experiment for the success of any RCT.

Blinding refers to keeping trial participants, health care providers, assessors or data collectors unaware of the assigned intervention, so that they will not be influenced by that knowledge. This process is conducted to minimize possible bias in implementation, dropouts, measurements, etc. Blinding is not always feasible for RCT but should be implemented if possible.

Randomization, allocation concealment and blinding should be well implemented and should be described in the paper.

On the other hand, many researchers are still unfamiliar with how to do randomization, and it has been shown that there are problems in many studies with the accurate performance of the randomization and that some studies are reporting incorrect results. So, we will introduce the recommended way of using statistical methods for a randomized controlled study and show how to report the results properly.

CATEGORIES OF RANDOMIZATION

Simple randomization.

The easiest method is simple randomization. If you assign subjects into two groups A and B, you assign subjects to each group purely randomly for every assignment. Even though this is the most basic way, if the total number of samples is small, sample numbers are likely to be assigned unequally. For this reason, we recommend you to use this method when the total number of samples is more than 100.

Block Randomization

We can create a block to assign sample numbers equally to each group and assign the block.

If we specify two in one block (the so-called block size is two), we can make two possible sequences of AB and BA. When we randomize them, the same sample numbers can be assigned to each group. If the block size is four, we can make six possible sequences; these are AABB, ABAB, ABBA, BAAB, BABA, BBAA, and we randomize them.

However, there is a disadvantage in that the executer can predict the next assignment. We can easily know the fact that B comes after A if the block size is two and if the block size is four; we can predict what every 4th sample is. This is discordant with the principle of randomization. To solve this problem, the allocator must hide the block size from the executer and use randomly mixed block sizes. For example, the block size can be two, four, and six.

Stratified Randomization

Randomization is important because it is almost the only way to assign all the other variables equally except for the factor (A and B) in which we are interested. However, some very important confounding variables can often be assigned unequally to the two groups. This possibility increases when the number of samples is smaller, and we can stratify the variables and assign the two groups equally in this case.

For example, if the smoking status is very important, what will you do? First, we have two methods of randomization that we learned previously. There are two randomly assigned separate sequences for smokers and non-smokers. Smokers are assigned to the smoker's sequences, and non-smokers are assigned to the non-smoker's sequences. Therefore, both smokers and non-smokers groups will be placed equally with the same numbers.

So we can use 'simple randomization with/without stratification' or 'block randomization with/without stratification.' However, if there are multiple stratified variables, it is difficult to place samples in both groups equally with the same numbers. Usually two or fewer stratified variables are recommended.

EXAMPLES OF RANDOMIZATION

Although there are websites or common programs for randomization, let us use an Excel file. Download the attached file in http://cafe.naver.com/easy2know/6427 . It is in a 'Read-only' state, but there is no limit in function; it is in the 'Read-only' state only to prevent accidental modification.

Due to the nature of Excel, if there is a change, it creates a new random number accordingly. If we input any number instead of '2' in the orange-colored cell and click the 'enter key,' it creates new random sequences ( Fig. 1 ). The sequences are the result of simple randomization. The numbers in the right column show the numbers of the total sample. Basically the numbers are up to 1,000, but if you need to, you can extend the numbers with the AutoFill function in Excel.

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Simple randomization sheet.

Fig. 2 shows an example of randomization when the block size is four. Also, there are numbers of the total samples in the right column.

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An example of randomization when the block size is four.

Fig. 3 shows an example of block randomization when the block size is two and four. Total eight kinds of blocks inside of the red-dotted line are assigned at random. The left column is for allocation and the right column is for the total sample size.

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Block randomization when the block size is two and four. Total eight blocks in the red-dotted line are assigned at random. The left column is for allocation and the right column is for the total sample size.

By the way, www.randomization.com can do block randomization for up to four kinds of block sizes and it is very easy to perform as well. Fig. 4 shows the general features and an example.

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www.randomization.com can do block randomization more easily. In this figure, the block size is 2, 4, and 6 when the total samples are 88.

THE REALITY OF THE RANDOMIZATION PROCEDURE

How to implement these techniques can vary by each trial. The following is only one of the examples of how these can be implemented in real trial. You may change the details of the example for your experiment. Figures of randomization and allocation concealment can also be adjusted to your needs ( Fig. 5 ).

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The reality of the randomization procedure.

Random Allocation

An independent researcher makes random allocation cards using computer-generated random numbers. He keeps the original random allocation sequences in an inaccessible third place and works with a copy. Since the executers can get confused with the original coding of A and B later, the allocator should record exactly what these codes mean to avoid further confusion.

When the purpose of the study is a surgical procedure, instead of using A and B, different names that distinguish exactly between the surgical procedures should be used (for example, 'the anterior approach' and 'the posterior approach'). It is convenient to reproduce the contents of the Excel file to a Word file, and enlarge the text font after replacing A with 'the anterior approach' (page break) and B with 'the posterior approach' (page break). Next, you print it out and put each of the sheets one by one into each envelope ( Fig. 6 ).

An external file that holds a picture, illustration, etc. Object name is cios-6-103-g006.jpg

MS word can replace A and B with a specific treatment name easily.

Here in Fig. 6 , '^m' is a special character for manual page break. After setting it as shown, you click 'all change' and print it out. Then we can get it printed per sheet. The inside of the envelope should not be visible from the outside, and it has to be printed out for each one and put in an envelope after being folded several times. In some papers, even aluminum foil was used to hide the print to prevent it from being read with a flash of light.

There are serial numbers on the outside of the envelopes. Input date, time, patient ID, results after the procedure, etc. usually will be recorded on the envelope or another sheet inside of the envelope, also.

Drug Preparation

An independent nurse (researcher) prepares syringes with "drug A" and "drug B" and puts them into envelopes according to the allocation orders. These syringes cannot be distinguished because they contain the same colored liquid with the same volume. Or pills or tablets with the same color and shape (placebo) will be put into the envelopes according to the allocation orders.

In the case of surgical treatment, an independent researcher prepares the envelopes, including writing the treatment name on a sheet of paper inside it. In the operation room, another independent nurse (researcher) opens the envelope and informs the doctor to do the treatment that is written on the paper in the envelope.

Another independent nurse injects the drug or the doctor performs the operation according to the order. The patient's ID, date, time and other information are recorded on each envelope. The nurse and the patient would not know what drugs are injected (double blinded). The doctor knows the treatment and the patient does not know it (one blinded). The preparer retrieves the envelopes and checks to see if the operation (and injection) was done as planned.

In the case of broken or lost syringes, the preparer figures out what the number of the envelope it is and replaces the envelope with the same drug according to the allocation.

The envelopes should be opened just before the injection or operation. For example, when a patient comes, an envelope is opened; however, if this does not meet the criteria for the performance of the study, this can be cancelled. Also, if the operator finds out before an operation the tool that is to be inserted, it is impossible to get the operation as planned. For example, even though plate A was assigned to be used, if the patient was indicated to have some other surgery because of infection or severe osteoporosis, you will waste an envelope and it will cause confusion as well as violate the randomization. All these cases should be mentioned as inclusion criteria and exclusion criteria in advance. To avoid this, the envelopes should be opened just before the operation or injection if possible.

However, in cases where the operation tool is so big that two tools cannot be prepared at the same time, or the preparation takes a lot of money (robotic surgery, etc.) or time (liver transplantation, etc.), the envelopes can be opened in advance.

Also, although you open an envelope and choose the procedure that you see, other conditions that affect the outcome can occur. For example, the patient could be admitted to the intensive care unit for medical problems after treatment, or may not get enough rehabilitation treatment for some other reasons.

In this case, it is an important issue whether to consider this as a follow-up loss or exclude this case from the study. We can deal with this issue by focusing on intention-to-treat analysis and per-protocol analysis. We will study this later when we get a chance.

Survey Results

After a period of time, another independent researcher measures the patient's outcome. He does not know the allocation. That is another blinding, so triple blinding is recommended if possible.

Another independent researcher who was not involved in any stage of these procedures will do the statistical analysis (sometimes a statistician). He even does not know the treatment name because the treatment name is hidden, as in A and B.

REPORTING OF RANDOMIZATION METHODS

From 1988 to 2000, 72 of 2,468 papers (2.9%) in the Journal of Born and Joint Surgery were RCTs. 1) It has been suggested that in some of the papers, randomization was not completely done or the result was not properly reported. According to the analysis of RCTs using painkillers from the January issue in 1966 to the June issue in 2006, 23.9% of the papers were inadequate in terms of the randomization. 2) It would be helpful to see a CONSORT checklist and examples. The following were used in the actual papers and extracted from examples in the CONSORT ( http://www.consort-statement.org ).

Sequence Generation

"Independent pharmacists dispensed either active or placebo inhalers according to a computer generated randomization list."

"For allocation of the participants, a computer-generated list of random numbers was used."

Type of Randomization

"Randomization sequence was created using Stata 9.0 (StataCorp, College Station, TX, USA) statistical software and was stratified by center with a 1:1 allocation using random block sizes of 2, 4, and 6."

"Participants were randomly assigned following simple randomization procedures (computerized random numbers) to 1 of 2 treatment groups."

We can apply the above examples to our case as follows: Randomization sequence was created using Excel 2007 (Microsoft, Redmond, WA, USA) with a 1:1 allocation using random block sizes of 2 and 4 by an independent doctor. In this way, sequence generation and type of randomization can be expressed at the same time.

Allocation Concealment Mechanism

"The doxycycline and placebo were in capsule form and identical in appearance. They were pre-packed in bottles and consecutively numbered for each woman according to the randomization schedule. Each woman was assigned an order number and received the capsules in the corresponding pre-packed bottle."

"The allocation sequence was concealed from the researcher (JR) enrolling and assessing participants in sequentially numbered, opaque, sealed and stapled envelopes. Aluminum foil inside the envelope was used to render the envelope impermeable to intense light. To prevent subversion of the allocation sequence, the name and date of birth of the participant was written on the envelope and a video tape made of the sealed envelope with participant details visible. Carbon paper inside the envelope transferred the information onto the allocation card inside the envelope and a second researcher (CC) later viewed video tapes to ensure envelopes were still sealed when participants' names were written on them. Corresponding envelopes were opened only after the enrolled participants completed all baseline assessments and it was time to allocate the intervention."

The second example was described in great detail, and we can guess how important the randomization and concealment were.

Who Generated the Allocation Sequence, Who Enrolled Participants, and Who Assigned Participants to Interventions?

"Determination of whether a patient would be treated by streptomycin and bed-rest (S case) or by bed-rest alone (C case) was made by reference to a statistical series based on random sampling numbers drawn up for each sex at each center by Professor Bradford Hill (this means that the stratification was done by sex and center); the details of the series were unknown to any of the investigators or to the coordinator. After acceptance of a patient by the panel, and before admission to the streptomycin center, the appropriate numbered envelope was opened at the central office; the card inside told, if the patient was to be an S or a C case, and this information was then given to the medical officer of the center."

"Details of the allocated group were given on colored cards contained in sequentially numbered, opaque, sealed envelopes. These were prepared at the NPEU and kept in an agreed location on each ward. Randomization took place at the end of the 2nd stage of labor when the midwife considered a vaginal birth was imminent. To enter a woman into the study, the midwife opened the next consecutively numbered envelope."

"Block randomization was by a computer generated random number list prepared by an investigator with no clinical involvement in the trial. We stratified by admission for an oncology related procedure. After the research nurse had obtained the patient's consent, she telephoned a contact who was independent of the recruitment process for allocation consignment."

If Done, Who Was Blinded after Assignment to Interventions and How

"Whereas patients and physicians allocated to the intervention group were aware of the allocated arm, outcome assessors and data analysts were kept blinded to the allocation."

"Blinding and equipoise were strictly maintained by emphasizing to intervention staff and participants that each diet adheres to healthy principles, and each of them is advocated by certain experts to be superior for long-term weight-loss. Except for the interventionists (dieticians and behavioral psychologists), investigators and staff were kept blind to diet assignment of the participants. The trial adhered to established procedures to maintain separation between staff that take outcome measurements and staff that deliver the intervention. Staffs who obtained outcome measurements were not informed of the diet group assignment. Intervention staffs, dieticians and behavioral psychologists who delivered the intervention did not take outcome measurements. All investigators, staffs, and participants were kept masked to outcome measurements and trial results."

In short, in a paper, we have to report who was kept blinded. In the case of physical therapy or surgery, keeping the surgeon blinded would be difficult or even impossible; however, blinding is possible for the person who measures the outcome. Anyhow, all individuals who were kept blinded must be described in the report.

WEBSITES AND SYSTEMS HELPING THESE PROCEDURES

To help with all the procedures of a fully qualified RCT, the following systems including electronic case report forms (eCRFs) are available for researchers.

iCReaT (clinical research and trial management system) in Korea Centers for Disease Control & Prevention (KCDC; http://icreat.nih.go.kr ): free for pre-educated and qualified researchers; there are regular education programs once a month, and some hospitals (for example, Severance Hospital) have their own educational programs. An English version will be available soon for non-Korean researchers.

MRCC ( https://mrcc.snuh.org ): for Seoul National University Hospital only. It is relatively inexpensive and includes statistical counseling.

Velos ( http://eresearch.ncc.re.kr ): a world-famous system and very expensive; it is available at National Cancer Center in Korea ( http://ncc.re.kr/crcc/ ).

eCRFs are very convenient as well as helpful to improve the quality of research and their advantages are summarized in the table ( Table 1 ).

Comparisons between Paper CRFs and e-CRFs of Web-based Clinical Research Management System

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CRF: case report form.

In RCT, random assignment is important and performing it is easy if you know how to do it. Besides the practice of randomization, correct reporting of the randomization process is also important and it should be done very accurately.

No potential conflict of interest relevant to this article was reported.

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Breathing control exercises delivered in a group setting for patients with chronic obstructive pulmonary disease: a randomized controlled trial.

what does random allocation control for

1. Introduction

2. materials and methods, 2.1. participants, 2.2. study design, 2.3. control group, 2.4. intervention group, 2.5. outcome measures, 2.6. statistical analysis, 3.1. participants, 3.2. primary outcome, 3.3. secondary outcomes, 4. discussion, 5. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Cazorla, S.; Busegnies, Y.; D’Ans, P.; Héritier, M.; Poncin, W. Breathing Control Exercises Delivered in a Group Setting for Patients with Chronic Obstructive Pulmonary Disease: A Randomized Controlled Trial. Healthcare 2023 , 11 , 877. https://doi.org/10.3390/healthcare11060877

Cazorla S, Busegnies Y, D’Ans P, Héritier M, Poncin W. Breathing Control Exercises Delivered in a Group Setting for Patients with Chronic Obstructive Pulmonary Disease: A Randomized Controlled Trial. Healthcare . 2023; 11(6):877. https://doi.org/10.3390/healthcare11060877

Cazorla, Sibylle, Yves Busegnies, Pierre D’Ans, Marielle Héritier, and William Poncin. 2023. "Breathing Control Exercises Delivered in a Group Setting for Patients with Chronic Obstructive Pulmonary Disease: A Randomized Controlled Trial" Healthcare 11, no. 6: 877. https://doi.org/10.3390/healthcare11060877

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IMAGES

  1. Random allocation carried out by a computer software

    what does random allocation control for

  2. Randomized controlled trial

    what does random allocation control for

  3. 12 Control Allocation scheme

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  4. Evidence-based trials: better compared than randomized

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  5. Random Allocation System

    what does random allocation control for

  6. 7.2 Managing confounding

    what does random allocation control for

COMMENTS

  1. A simplified guide to randomized controlled trials

    A randomized controlled trial is a prospective, comparative, quantitative study/experiment performed under controlled conditions with random allocation of interventions to comparison groups. The randomized controlled trial is the most rigorous and robust research method of determining whether a caus …

  2. Random Selection & Random Allocation: Differences, Benefits & Examples

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  4. What does randomisation achieve?

    What are the benefits of random allocation in clinical studies? John Worrall, a philosopher of science, recently questioned whether evidence-based medicine's advice to base therapeutic decisions on the results of randomised controlled trials (RCTs) could be justified.1 2 Here we provide a response to Worrall and others who challenge the epistemological value of RCTs. Worrall's primary target ...

  5. Controlled Experiment

    Random Allocation Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition. The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.

  6. Conducting the Study: Randomization and Allocation

    Random allocation is another paramount method used to assign participants to different research groups (Peat, 2011). In other words, randomization is a practice that's used to achieve generalizability, while random allocation - is to minimize confounders and eliminate systematic bias.

  7. What is a Randomized Control Trial (RCT) Study?

    DA randomized control trial (RCT) is a type of study design that involves randomly assigning participants to either an experimental group or a control group. How They Work Advantages Limitations Fictitious Example Real-life Examples References How They Work

  8. What random assignment does and does not do

    Random assignment of patients to comparison groups stochastically tends, with increasing sample size or number of experiment replications, to minimize the confounding of treatment outcome differences by the effects of differences among these groups in unknown/unmeasured patient characteristics.

  9. Control: Random Allocation and Counterbalancing ...

    Define random allocation. An attempt to control for participant variables in an independent groups design which ensures that each participant has the same chance of being in one condition as the other.

  10. The difference between allocation concealment and blinding in

    In a clinical trial, random allocation is needed so that participants in treatment and control groups are similar at baseline. This allows us to conclude whether results observed are due to differences in treatment, rather than differences in baseline characteristics between groups.

  11. How to randomise

    We have explained why random allocation of treatments is a required feature of controlled trials.1 Here we consider how to generate a random allocation sequence. Almost always patients enter a trial in sequence over a prolonged period. In the simplest procedure, simple randomisation, we determine each patient's treatment at random independently with no constraints. With equal allocation to two ...

  12. Allocation concealment in randomised controlled trials: are ...

    A robust randomised controlled trial (RCT) must use allocation concealment—that is, separate the act of randomisation from the person recruiting participants. Poor randomisation methods cause exaggerated treatment effects, are open to subversion by researchers or clinicians, and have a knock-on effect on systematic reviews. 1 2 3

  13. CIOS :: Clinics in Orthopedic Surgery

    Random allocation is a technique that chooses individuals for treatment groups and control groups entirely by chance with no regard to the will of researchers or patients' condition and preference. This allows researchers to control all known and unknown factors that may affect results in treatment groups and control groups. Allocation ...

  14. Allocation concealment: the key to effective randomisation

    Randomisation and allocation concealment Randomisation - the process of assigning participants to groups so that each participant has an equal chance of being assigned to a given group - is often used in medical research. It ensures different groups being studied have similar characteristics when the study begins, allowing a fair comparison.

  15. Research Control

    Research Control. There are several ways in which research can be controlled to eliminate extraneous variables. Random allocation of participants is an extremely important process in research. In order to assess the effect of one variable on another, all variables other than the variable to be investigated need to be controlled.

  16. PDF How to Do Random Allocation (Randomization)

    Random allocation is a technique that chooses individuals for treatment groups and control groups entirely by chance with no regard to the will of researchers or patients' con-dition and preference.

  17. Allocation concealment

    Allocation concealment. In a randomized experiment, allocation concealment hides the sorting of trial participants into treatment groups so that this knowledge cannot be exploited. Adequate allocation concealment serves to prevent study participants from influencing treatment allocations for subjects. Studies with poor allocation concealment ...

  18. The Definition of Random Assignment In Psychology

    Random assignment refers to the use of chance procedures in psychology experiments to ensure that each participant has the same opportunity to be assigned to any given group. Study participants are randomly assigned to different groups, such as the experimental group or treatment group. Overview

  19. Random allocation

    random allocation: In a clinical trial, the assignment of subjects or patients to treatment (or control) groups in an unpredictable fashion. In a blinded study, assignment sequences are concealed, but can be disclosed in the event of adverse events.

  20. What is Allocation Concealment?

    Allocation Concealment is a technique used to prevent selection bias in Randomised Controlled Trials (RCT's) by concealing the allocation sequence from those assigning participants to the intervention groups, until the moment of assignment.

  21. National Center for Biotechnology Information

    National Center for Biotechnology Information

  22. Healthcare

    Breathing control exercises are an important component of occupational therapy in patients with chronic obstructive pulmonary disease (COPD). Delivering these exercises in group settings may enhance their benefits. Therefore, this study assessed the effectiveness of breathing control exercises delivered in a group format to patients with severe COPD remitting from an acute pulmonary ...