The performance of marginal structural models for estimating risk differences and relative risks using weighted univariate generalized linear models
Austin PC. Stat Methods Med Res. 2024; Apr 24 [Epub ahead of print].
Objective — Statisticians have criticized the use of significance testing to compare the distribution of baseline covariates between treatment groups in randomized controlled trials (RCTs). Furthermore, some have advocated for the use of regression adjustment to estimate the effect of treatment after adjusting for potential imbalances in prognostically important baseline covariates between treatment groups.
Study Design and Setting — We examined 114 RCTs published in the New England Journal of Medicine, the Journal of the American Medical Association, The Lancet, and the British Medical Journal between January 1, 2007 and June 30, 2007.
Results — Significance testing was used to compare baseline characteristics between treatment arms in 38% of the studies. The practice was very rare in British journals and more common in the U.S. journals. In 29% of the studies, the primary outcome was continuous, whereas in 65% of the studies, the primary outcome was either dichotomous or time-to-event in nature. Adjustment for baseline covariates was reported when estimating the treatment effect in 34% of the studies.
Conclusions — Our findings suggest the need for greater editorial consistency across journals in the reporting of RCTs. Furthermore, there is a need for greater debate about the relative merits of unadjusted vs. adjusted estimates of treatment effect.
Austin PC, Manca A, Zwarenstein M, Juurlink DN, Stanbrook MB. J Clin Epidemiol. 2010; 63(2):142-53. Epub 2009 Aug 27.
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