Clinicians are typically interested in the effects of medical interventions that apply to individual patients. Such individual effects are conditional effects rather than marginal (or population averaged) effects. When considering odds ratios, conditional (adjusted) and marginal (crude) effects may differ, even in a randomized trial with perfectly balanced baseline covariates, due to non-collapsibility of the odds ratio. Using a numerical example, we explained this phenomenon of non-collapsibility of the odds ratio and showed that the difference between conditional and marginal odds ratios depends on the strength of the association between a third (stratifying) variable and the outcome, as well as on the distribution of this stratifying variable in the trial population. Risk ratios are not affected by non-collapsibility and therefore, conditional and marginal risk ratios are the same when adjusting for well balanced baseline covariates in randomized trials. Reports on randomized trials should more often include treatment effects that are expressed as risk ratios rather than odds ratios. When odds ratios are used, adjustment for baseline covariates should be considered, also when these are well-balanced between the treatment groups.
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