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Korean Journal of Anesthesiology Jun 2019Randomized controlled trial is widely accepted as the best design for evaluating the efficacy of a new treatment because of the advantages of randomization (random... (Review)
Review
Randomized controlled trial is widely accepted as the best design for evaluating the efficacy of a new treatment because of the advantages of randomization (random allocation). Randomization eliminates accidental bias, including selection bias, and provides a base for allowing the use of probability theory. Despite its importance, randomization has not been properly understood. This article introduces the different randomization methods with examples: simple randomization; block randomization; adaptive randomization, including minimization; and response-adaptive randomization. Ethics related to randomization are also discussed. The study is helpful in understanding the basic concepts of randomization and how to use R software.
Topics: Bias; Humans; Random Allocation; Randomized Controlled Trials as Topic; Research Design; Selection Bias
PubMed: 30929415
DOI: 10.4097/kja.19049 -
International Journal of Environmental... Jan 2011When planning a randomized clinical trial, careful consideration must be given to how participants are selected for various arms of a study. Selection and accidental...
When planning a randomized clinical trial, careful consideration must be given to how participants are selected for various arms of a study. Selection and accidental bias may occur when participants are not assigned to study groups with equal probability. A simple random allocation scheme is a process by which each participant has equal likelihood of being assigned to treatment versus referent groups. However, by chance an unequal number of individuals may be assigned to each arm of the study and thus decrease the power to detect statistically significant differences between groups. Block randomization is a commonly used technique in clinical trial design to reduce bias and achieve balance in the allocation of participants to treatment arms, especially when the sample size is small. This method increases the probability that each arm will contain an equal number of individuals by sequencing participant assignments by block. Yet still, the allocation process may be predictable, for example, when the investigator is not blind and the block size is fixed. This paper provides an overview of blocked randomization and illustrates how to avoid selection bias by using random block sizes.
Topics: Bias; Humans; Random Allocation; Randomized Controlled Trials as Topic; Sample Size; Selection Bias
PubMed: 21318011
DOI: 10.3390/ijerph8010015 -
Family Medicine Feb 2007Randomization in randomized controlled trials involves more than generation of a random sequence by which to assign subjects. For randomization to be successfully...
Randomization in randomized controlled trials involves more than generation of a random sequence by which to assign subjects. For randomization to be successfully implemented, the randomization sequence must be adequately protected (concealed) so that investigators, involved health care providers, and subjects are not aware of the upcoming assignment. The absence of adequate allocation concealment can lead to selection bias, one of the very problems that randomization was supposed to eliminate. Authors of reports of randomized trials should provide enough details on how allocation concealment was achieved so the reader can determine the likelihood of success. Fortunately, a plan of allocation concealment can always be incorporated into the design of a randomized trial. Certain methods minimize the risk of concealment failing more than others. Keeping knowledge of subjects' assignment after allocation from subjects, investigators/health care providers, or those assessing outcomes is referred to as masking (also known as blinding). The goal of masking is to prevent ascertainment bias. In contrast to allocation concealment, masking cannot always be incorporated into a randomized controlled trial. Both allocation concealment and masking add to the elimination of bias in randomized controlled trials.
Topics: Humans; Random Allocation; Randomized Controlled Trials as Topic; Selection Bias; United States
PubMed: 17273956
DOI: No ID Found -
Kidney International Feb 2008As confounding obscures the 'real' effect of an exposure on outcome, investigators performing etiological studies do their utmost best to prevent or control confounding....
As confounding obscures the 'real' effect of an exposure on outcome, investigators performing etiological studies do their utmost best to prevent or control confounding. Unfortunately, in this process, errors are frequently made. This paper explains that to be a potential confounder, a variable needs to satisfy all three of the following criteria: (1) it must have an association with the disease, that is, it should be a risk factor for the disease; (2) it must be associated with the exposure, that is, it must be unequally distributed between exposure groups; and (3) it must not be an effect of the exposure; this also means that it may not be part of the causal pathway. In addition, a number of different techniques are described that may be applied to prevent or control for confounding: randomization, restriction, matching, and stratification. Finally, a number of examples outline commonly made errors, most of which result from 'overadjustment' for variables that do not satisfy the criteria for potential confounders. Such an example of an error frequently occurring in the literature is the incorrect adjustment for blood pressure while studying the relationship between body mass index and the development of end-stage renal disease. Such errors will introduce new bias instead of preventing it.
Topics: Confounding Factors, Epidemiologic; Humans; Kidney Diseases; Random Allocation
PubMed: 17978811
DOI: 10.1038/sj.ki.5002650 -
BMJ (Clinical Research Ed.) Jun 1991
Topics: Bias; Random Allocation; Randomized Controlled Trials as Topic
PubMed: 1855013
DOI: 10.1136/bmj.302.6791.1481 -
Journal of Pharmacy & Pharmaceutical... 2014An allocation strategy that allows for chance placement of participants to study groups is crucial to the experimental nature of randomised controlled trials. Following... (Review)
Review
PURPOSE
An allocation strategy that allows for chance placement of participants to study groups is crucial to the experimental nature of randomised controlled trials. Following decades of the discovery of randomisation considerable erroneous opinion and misrepresentations of its concept both in principle and practice still exists. In some circles, opinions are also divided on the strength and weaknesses of each of the random allocation strategies. This review provides an update on various random allocation techniques so as to correct existing misconceptions on this all important procedure.
METHODS
This is a review of literatures published in the Pubmed database on concepts of common allocation techniques used in controlled clinical trials.
RESULTS
Allocation methods that use; case record number, date of birth, date of presentation, haphazard or alternating assignment are non-random allocation techniques and should not be confused as random methods. Four main random allocation techniques were identified. Minimisation procedure though not fully a random technique, however, proffers solution to the limitations of stratification at balancing for multiple prognostic factors, as the procedure makes treatment groups similar in several important features even in small sample trials.
CONCLUSIONS
Even though generation of allocation sequence by simple randomisation procedure is easily facilitated, a major drawback of the technique is that treatment groups can by chance end up being dissimilar both in size and composition of prognostic factors. More complex allocation techniques that yield more comparable treatment groups also have certain drawbacks. However, it is important that whichever allocation technique is employed, unpredictability of random assignment should not be compromised.
Topics: Humans; Random Allocation; Randomized Controlled Trials as Topic
PubMed: 24934553
DOI: 10.18433/j3sw36 -
Journal of the Royal Society, Interface Feb 2018In empirical studies, trajectories of animals or individuals are sampled in space and time. Yet, it is unclear how sampling procedures bias the recorded data. Here, we...
In empirical studies, trajectories of animals or individuals are sampled in space and time. Yet, it is unclear how sampling procedures bias the recorded data. Here, we consider the important case of movements that consist of alternating rests and moves of random durations and study how the estimate of their statistical properties is affected by the way we measure them. We first discuss the ideal case of a constant sampling interval and short-tailed distributions of rest and move durations, and provide an exact analytical calculation of the fraction of correctly sampled trajectories. Further insights are obtained with simulations using more realistic long-tailed rest duration distributions showing that this fraction is dramatically reduced for real cases. We test our results for real human mobility with high-resolution GPS trajectories, where a constant sampling interval allows one to recover at best 18% of the movements, while over-evaluating the average trip length by a factor of 2. Using a sampling interval extracted from real communication data, we recover only 11% of the moves, a value that cannot be increased above 16% even with ideal algorithms. These figures call for a more cautious use of data in quantitative studies of individuals' movements.
Topics: Algorithms; Female; Humans; Male; Models, Biological; Random Allocation; Walking
PubMed: 29436509
DOI: 10.1098/rsif.2017.0776 -
Journal of Indian Prosthodontic Society Jan 2024
Topics: Random Allocation
PubMed: 38263552
DOI: 10.4103/jips.jips_545_23 -
Tidsskrift For Den Norske Laegeforening... Oct 2018
Topics: Humans; Random Allocation
PubMed: 30378409
DOI: 10.4045/tidsskr.18.0555 -
Clinical Infectious Diseases : An... Aug 2021
Topics: Humans; Motivation; Random Allocation; Sample Size
PubMed: 32702084
DOI: 10.1093/cid/ciaa1027