Covariate adjustments in randomized controlled trials increased study power and reduced biasedness of effect size estimation
Covariate adjustments in randomized controlled trials increased study power and reduced biasedness of effect size estimation
Objectives This study aims to show that under several assumptions, in randomized controlled trials (RCTs), unadjusted, crude analysis will underestimate the Cohen's d effect size of the treatment, and an unbiased estimate of effect size can be obtained only by adjusting for all predictors of the outcome. Study Design and Setting Four simulations were performed to examine the effects of adjustment on the estimated effect size of the treatment and power of the analysis. In addition, we analyzed data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (older adults aged 65–94), an RCT with three treatment arms and one control arm. Results We showed that (1) the number of unadjusted covariates was associated with the effect size of the treatment; (2) the biasedness of effect size estimation was minimized if all covariates were adjusted for; (3) the power of the statistical analysis slightly decreased with the number of adjusted noise variables; and (4) exhaustively searching the covariates and noise variables adjusted for can lead to exaggeration of the true effect size. Analysis of the ACTIVE study data showed that the effect sizes adjusting for covariates of all three treatments were 7.39–24.70% larger than their unadjusted counterparts, whereas the effect size would be elevated by at most 57.92% by exhaustively searching the variables adjusted for. Conclusion All covariates of the outcome in RCTs should be adjusted for, and if the effect of a particular variable on the outcome is unknown, adjustment will do more good than harm.
Adjustment, Cohen's d effect size, Covariates, Data analysis, Epidemiology, Trials
137-146
Lee, Paul H.
02620eab-ae7f-4a1c-bad1-8a50e7e48951
1 August 2016
Lee, Paul H.
02620eab-ae7f-4a1c-bad1-8a50e7e48951
Lee, Paul H.
(2016)
Covariate adjustments in randomized controlled trials increased study power and reduced biasedness of effect size estimation.
Journal of Clinical Epidemiology, 76 (8), .
(doi:10.1016/j.jclinepi.2016.02.004).
Abstract
Objectives This study aims to show that under several assumptions, in randomized controlled trials (RCTs), unadjusted, crude analysis will underestimate the Cohen's d effect size of the treatment, and an unbiased estimate of effect size can be obtained only by adjusting for all predictors of the outcome. Study Design and Setting Four simulations were performed to examine the effects of adjustment on the estimated effect size of the treatment and power of the analysis. In addition, we analyzed data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (older adults aged 65–94), an RCT with three treatment arms and one control arm. Results We showed that (1) the number of unadjusted covariates was associated with the effect size of the treatment; (2) the biasedness of effect size estimation was minimized if all covariates were adjusted for; (3) the power of the statistical analysis slightly decreased with the number of adjusted noise variables; and (4) exhaustively searching the covariates and noise variables adjusted for can lead to exaggeration of the true effect size. Analysis of the ACTIVE study data showed that the effect sizes adjusting for covariates of all three treatments were 7.39–24.70% larger than their unadjusted counterparts, whereas the effect size would be elevated by at most 57.92% by exhaustively searching the variables adjusted for. Conclusion All covariates of the outcome in RCTs should be adjusted for, and if the effect of a particular variable on the outcome is unknown, adjustment will do more good than harm.
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Accepted/In Press date: 17 February 2016
Published date: 1 August 2016
Additional Information:
Funding Information:
Funding: The ACTIVE intervention trials are supported by grants from the National Institute on Aging and the National Institute of Nursing Research to Hebrew Senior Life ( U01NR04507 ), Indiana University School of Medicine ( U01NR04508 ), Johns Hopkins University ( U01AG14260 ), New England Research Institutes ( U01AG14282 ), Pennsylvania State University ( U01AG14263 ), the University of Alabama at Birmingham ( U01AG14289 ), and the University of Florida ( U01AG14276 ). Inferences expressed here are those of the authors and are not necessarily reflective of the academic or funding agencies involved.
Publisher Copyright:
© 2016 Elsevier Inc.
Keywords:
Adjustment, Cohen's d effect size, Covariates, Data analysis, Epidemiology, Trials
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Local EPrints ID: 475159
URI: http://eprints.soton.ac.uk/id/eprint/475159
ISSN: 0895-4356
PURE UUID: 9eb27955-99e6-483f-a4c1-8baafaf70779
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Date deposited: 10 Mar 2023 17:47
Last modified: 18 Mar 2024 04:09
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Author:
Paul H. Lee
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