Analysis of 1:1 Matched Cohort Studies and Twin Studies, with Binary Exposures and Binary Outcomes

TL;DR

This paper reviews analysis methods for matched cohort and twin studies with binary exposures and outcomes, focusing on target parameters, assumptions, and statistical power comparisons.

Contribution

It provides a comprehensive overview of analysis techniques for matched cohort and twin studies, highlighting differences and considerations specific to these designs.

Findings

Clarifies target parameters in common analysis methods

Discusses assumptions underlying each method

Compares statistical power across methods

Abstract

To improve confounder adjustments, observational studies are often matched on potential confounders. While matched case-control studies are common and well covered in the literature, our focus here is on matched cohort studies, which are less common and sparsely discussed in the literature. Matched data also arise naturally in twin studies, as a cohort of exposure-discordant twins can be viewed as being matched on a large number of potential confounders. The analysis of twin studies will be given special attention. We give an overview of various analysis methods for matched cohort studies with binary exposures and binary outcomes. In particular, our aim is to answer the following questions: (1) What are the target parameters in the common analysis methods? (2) What are the underlying assumptions in these methods? (3) How do the methods compare in terms of statistical power?