Sensitivity of results to sample size and covariate prevalence
Reducing the sample size from 1000 to 200 resulted in larger empirical standard errors and reduced power across all methods as expected (results not shown). It had little impact on analyses based on the true strata otherwise and little impact on bias for any method. In contrast, the smaller sample size reduced but did not eliminate the undercoverage observed when estimating treatment effects using the updated strata (Supplementary Figure Increasing the covariate prevalence from 0.5 to 0.75 introduced bias and undercoverage into the treatment effect estimate based on the updated strata in the setting where errors were equal across strata but error discovery was unequal across treatment groups (Supplementary Figure 