Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We study the properties of imbalances tests of predetermined characteristics (covariates) in stratified randomized controlled trials. When the parameter of interest is a weighted average of the causal effects at all strata, then a test statistic based on a fixed effects regression model may suffice to detect the relevant imbalances. This will be true under a condition on the partial correlation between covariates and the outcome variable (uniformity condition). If that condition is violated, then the test based on the fixed effects regression will lack power. In that case, a test based on the fully saturated regression model can overcome this problem. Finally, we provide an omnibus test for the relevance of controlling for the covariates when estimating the average treatment effect (ATE).