Document Detail


Statistical properties of randomization in clinical trials.
MedLine Citation:
PMID:  3060315     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This is the first of five articles on the properties of different randomization procedures used in clinical trials. This paper presents definitions and discussions of the statistical properties of randomization procedures as they relate to both the design of a clinical trial and the statistical analysis of trial results. The subsequent papers consider, respectively, the properties of simple (complete), permuted-block (i.e., blocked), and urn (adaptive biased-coin) randomization. The properties described herein are the probabilities of treatment imbalances and the potential effects on the power of statistical tests; the permutational basis for statistical tests; and the potential for experimental biases in the assessment of treatment effects due either to the predictability of the random allocations (selection bias) or the susceptibility of the randomization procedure to covariate imbalances (accidental bias). For most randomization procedures, the probabilities of overall treatment imbalances are readily computed, even when a stratified randomization is used. This is important because treatment imbalance may affect statistical power. It is shown, however, that treatment imbalance must be substantial before power is more than trivially affected. The differences between a population versus a permutation model as a basis for a statistical test are reviewed. It is argued that a population model can only be invoked in clinical trials as an untestable assumption, rather than being formally based on sampling at random from a population. On the other hand, a permutational analysis based on the randomization actually employed requires no assumptions regarding the origin of the samples of patients studied. The large sample permutational distribution of the family of linear rank tests is described as a basis for easily conducting a variety of permutation tests. Subgroup (stratified) analyses, analyses when some data are missing, and regression model analyses are also discussed. The Blackwell-Hodges model for selection bias in the composition of the study groups is described. The expected selection bias associated with a randomization procedure is a function of the predictability of the treatment allocations and is readily evaluated for any sequence of treatment assignments. In an unmasked study, the potential for selection bias may be substantial with highly predictable sequences. Finally, the Efron model for accidental bias in the estimate of treatment effect in a linear model is described. This is important because the potential for accidental bias is equivalent to the potential for a covariate imbalance.(ABSTRACT TRUNCATED AT 400 WORDS)
Authors:
J M Lachin
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S.; Review    
Journal Detail:
Title:  Controlled clinical trials     Volume:  9     ISSN:  0197-2456     ISO Abbreviation:  Control Clin Trials     Publication Date:  1988 Dec 
Date Detail:
Created Date:  1989-02-03     Completed Date:  1989-02-03     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8006242     Medline TA:  Control Clin Trials     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  289-311     Citation Subset:  IM    
Affiliation:
George Washington University, Department of Statistics/Computer and Information Systems, Rockville, Maryland 20852.
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MeSH Terms
Descriptor/Qualifier:
Clinical Trials as Topic / methods*
Data Interpretation, Statistical*
Humans
Models, Statistical
Random Allocation*
Research Design*
Grant Support
ID/Acronym/Agency:
R01-AM-27769/AM/NIADDK NIH HHS; R01-DK-39826/DK/NIDDK NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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