Using Propensity Scores for Causal Inference: Pitfalls and Tips
Author:
Affiliation:
1. Department of Epidemiology, Harvard T.H. Chan School of Public Health
2. Clinical Research Promotion Center, The University of Tokyo Hospital
Publisher
Japan Epidemiological Association
Subject
General Medicine,Epidemiology
Link
https://www.jstage.jst.go.jp/article/jea/31/8/31_JE20210145/_pdf
Reference49 articles.
1. 1. Glass TA, Goodman SN, Hernán MA, Samet JM. Causal inference in public health. Annu Rev Public Health. 2013;34:61–75.
2. 2. Hernán MA, Robins JM. Causal Inference: What If. Boca Raton: Chapman & Hall/CRC; 2020.
3. 3. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424.
4. 4. Rubin DB. Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol. 1974;66(5):688–701.
5. 5. Petersen ML, van der Laan MJ. Causal models and learning from data: integrating causal modeling and statistical estimation. Epidemiology. 2014;25(3):418–426.
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