A few years ago I was working on a paper about covariate adjustment in randomised trials, when a colleague working on a SAP (statistical analysis plan) for a trial approached me: “you say what a good idea covariate adjustment is but…” she said, followed by several practical questions about how you choose an adjustment method and pre-specify it in a SAP.
Maybe this is all consistent with the recommendation to not use odds ratios as estimands? Or is it just that it is impossible to convince researchers to stop using them?
This affects collapsible measures too! It’s just that there’s a safety net: if we think we’re targeting a conditional measure and forcing it to be the same for all x then at least readers can be reassured that it’s targeting the marginal measure.
Maybe this is all consistent with the recommendation to not use odds ratios as estimands? Or is it just that it is impossible to convince researchers to stop using them?
This affects collapsible measures too! It’s just that there’s a safety net: if we think we’re targeting a conditional measure and forcing it to be the same for all x then at least readers can be reassured that it’s targeting the marginal measure.