Which of the following is an example of a multivariate analytical model to examine exposure variables with disease outcomes?

• A. Kaplan-Meier estimation
• B. Mantel-Haenszel stratified analysis
• C. Cox proportional hazards model
• D. Wilcoxon rank-sum test

Answer: (B)

Multivariate analytical models adjust for multiple covariates to isolate the effect of an exposure on disease outcomes. The Cox proportional hazards model is a prime example: it handles time-to-event data and lets you include several covariates (such as exposure, age, sex, and other risk factors) to estimate hazard ratios that reflect the exposure’s independent effect while controlling for others. This is the key reason it’s the best choice for examining how an exposure relates to disease when time to event matters and you need to account for multiple factors at once. Kaplan-Meier estimation, by contrast, describes survival without adjusting for covariates. The Mantel-Haenszel method provides a pooled effect across strata of a single confounder and isn’t a regression-based multivariate model. The Wilcoxon rank-sum test compares groups without adjusting for other variables.