PSweight: An R Package for Propensity Score Weighting Analysis
Abstract
Propensity score weighting is an important tool for comparative effectiveness research.Besides the inverse probability of treatment weights (IPW), recent development has introduced a general class of balancing weights, corresponding to alternative target populations and estimands. In particular, the overlap weights (OW) lead to optimal covariate balance and estimation efficiency, and a target population of scientific and policy interest. We develop the R package PSweight to provide a comprehensive design and analysis platform for causal inference based on propensity score weighting. PSweight supports (i) a variety of balancing weights, (ii) binary and multiple treatments,(iii) simple and augmented weighting estimators, (iv) nuisance-adjusted sandwich variances, and(v) ratio estimands. PSweight also provides diagnostic tables and graphs for covariate balance assessment. We demonstrate the functionality of the package using a data example from the NationalChild Development Survey (NCDS), where we evaluate the causal effect of educational attainment on income.
Cite
@article{arxiv.2010.08893,
title = {PSweight: An R Package for Propensity Score Weighting Analysis},
author = {Tianhui Zhou and Guangyu Tong and Fan Li and Laine E. Thomas and Fan Li},
journal= {arXiv preprint arXiv:2010.08893},
year = {2022}
}
Comments
18 pages, 3 figures, 5 tables