Propensity Score Methods For Causal Inference: An Overview
Keywords
IPTW; Propensity score analysis; Propensity score matching; Propensity score methods; Propensity scores; Subclassification
Abstract
Propensity score methods are popular and effective statistical techniques for reducing selection bias in observational data to increase the validity of causal inference based on observational studies in behavioral and social science research. Some methodologists and statisticians have raised concerns about the rationale and applicability of propensity score methods. In this review, we addressed these concerns by reviewing the development history and the assumptions of propensity score methods, followed by the fundamental techniques of and available software packages for propensity score methods. We especially discussed the issues in and debates about the use of propensity score methods. This review provides beneficial information about propensity score methods from the historical point of view and helps researchers to select appropriate propensity score methods for their observational studies.
Publication Date
10-1-2018
Publication Title
Behaviormetrika
Volume
45
Issue
2
Number of Pages
317-334
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s41237-018-0058-8
Copyright Status
Unknown
Socpus ID
85074757520 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85074757520
STARS Citation
Pan, Wei and Bai, Haiyan, "Propensity Score Methods For Causal Inference: An Overview" (2018). Scopus Export 2015-2019. 9600.
https://stars.library.ucf.edu/scopus2015/9600