This article focuses on the implementation of propensity score matching for clustered data. Different approaches to reduce bias due to cluster-level confounders are considered and compared using Monte Carlo simulations. ...
Using an extensive simulation exercise, we address two open issues in propensity score
analyses: how to estimate propensity scores and how to assess covariates balance. We
compare the performance of several machine ...
Cannas, Massimo; Arpino, Bruno(The R Foundation, 2019)
Matching is a well known technique to balance covariates distribution between treated and control units in non-experimental studies. In many fields, clustered data are a very common occurrence in the analysis of observational ...
