Covariate adjustment in RCTs results in increased power to detect conditional effects compared with the power to detect unadjusted or marginal effects-Reference-Cited by-同舟云学术

Covariate adjustment in RCTs results in increased power to detect conditional effects compared with the power to detect unadjusted or marginal effects

Published:2010-12 Issue:12 Volume:63 Page:1392-1393
ISSN:0895-4356
Container-title:Journal of Clinical Epidemiology
language:en
Short-container-title:Journal of Clinical Epidemiology

Author:

Austin Peter C.,Manca Andrea,Zwarenstein Merrick,Juurlink David N.,Stanbrook Matthew B.

Funder

Institute for Clinical Evaluative Sciences (ICES)

Ontario Ministry of Health and Long-Term Care (MOHLTC)

Heart and Stroke Foundation of Ontario

Publisher

Elsevier BV

Subject

Epidemiology

Reference7 articles.

1. Covariate adjustment increases statistical power in randomized controlled trials;Lingsma;J Clin Epidemiol,2010

2. A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals;Austin;J Clin Epidemiol,2010

3. Clinical prediction models: a practical approach to development, validation, and updating;Steyerberg,2009

4. Interpretation and choice of effect measures in epidemiologic analyses;Greenland;Am J Epidemiol,1987

5. Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates;Gail;Biometrika,1984

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