What is the primary purpose of stratified analysis in detecting effect modification?

• A. To estimate stratum-specific estimates of the exposure effect
• B. To maximize overall pooled effect size
• C. To avoid stratification altogether
• D. To validate data with separate sample

Answer: (A)

Effect modification happens when the impact of an exposure on an outcome changes across levels of another variable. Stratified analysis tackles this by estimating the exposure effect within each level of that variable. By looking at these stratum-specific effects, you can see whether the association is consistent or varies between groups. If the estimates differ across strata, that indicates the effect is modified by the stratifying factor. This approach directly reveals how the exposure’s impact changes in different subgroups, rather than producing one overall pooled effect. That’s why the main purpose is to estimate stratum-specific estimates of the exposure effect. The other ideas—maximizing a single pooled effect, avoiding stratification, or using separate samples for validation—do not address detecting how the effect changes across subgroups.