 Solution

Matching controls strong prognostic differences between patients and can greatly improve precision by making treatment comparisons within homogeneous pairs. It also protects against confounding when treatment assignment is not perfectly randomized globally.

Its disadvantage is loss of information: pairs with censoring before a comparison or tied outcomes contribute little or nothing, and the analysis cannot estimate the effects of pair-level matching variables. Poor matches and the logistics of paired enrollment can also reduce efficiency relative to a well-adjusted unpaired analysis.