Performance of modeling and balancing approach methods when using weights to estimate treatment effects in observational time-to-event settings.

ABSTRACT: In observational studies weighting techniques are often used to overcome bias due to confounding. Modeling approaches, such as inverse propensity score weighting, are popular, but often rely on the correct specification of a parametric model wherein neither balance nor stability are targeted. More recently, balancing approach methods that directly target covariate imbalances have been proposed, and these allow the researcher to explicitly set the desired balance constraints. In this study, we evaluate the finite sample properties of different modeling and balancing approach methods, when estimating the marginal hazard ratio, through Monte Carlo simulations. The use of the different methods is also illustrated by analyzing data from the Swedish stroke register to estimate the effect of pres

SUBMITTER: Barros GWF 

PROVIDER: S-EPMC10703278 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature