Adjustment for baseline characteristics in randomized trials using logistic regression: sample-based model versus true model.

ABSTRACT:

Background

Adjustment for baseline prognostic factors in randomized clinical trials is usually performed by means of sample-based regression models. Sample-based models may be incorrect due to overfitting. To assess whether overfitting is a problem in practice, we used simulated data to examine the performance of the sample-based model in comparison to a "true" adjustment model, in terms of estimation of the treatment effect.

Methods

We conducted a simulation study using samples drawn from a "population" in which both the treatment effect and the effect of the potential confounder were specified. The outcome variable was binary. Using logistic regression, we compared three estimates of the treatment effect in each situation: unadjusted, adjusted for the confounder using the

SUBMITTER: Perneger T 

PROVIDER: S-EPMC9924183 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature