A Review of Causality in a Social World: Moderation,Mediation,and Spill-Over

Austin P. C. Jembere N. Chiu M. (2016). Propensity score matching and complex surveys. Statistical Methods in Medical Research. doi:10.117/0962280216658920

Dong N. (2015). Using propensity score methods to approximate factorial experimental designs to analyze the relationship between two variables and an outcome. American Journal of Evaluation, 36, 42–66. doi:10.1177/1098214014553261

Egami N. Imai K. (2018). Causal interaction in factorial experiments: Application to conjoint analysis. Journal of the American Statistical Association. Advance online publication. doi:10.1080/01621459.2018.1476246

Hong G. (2015). Causality in a social world: Moderation, mediation, and spill-over. West Sussex, England: Wiley-Blackwell.

Lenis D. Nguyen T. Q. Dong N. Stuart E. A. (2017). It’s all about balance: Propensity score matching in the context of complex survey data. Biostatistics. Advance online publication. doi:10.1093/biostatistics/kxx063

Neyman J. (1923/1990). On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Translated in Statistical Science, 5, 465–472.

Ridgeway G. Kovalchik S. A. Griffin B. A. Kabeto M. U. (2015). Propensity score analysis with survey weighted data. Journal of Causal Inference, 3, 237–249. doi:10.1515/jci-2014-0039

Rubin D. B. (1980). Discussion of “randomization analysis of experimental data in the Fisher randomization test” by Basu. Journal of the American Statistical Association, 75, 591–593.

Weiss M. J. Bloom H. S. Brock T. (2014). A conceptual framework for studying the sources of variation in program effects. Journal of Policy Analysis and Management, 3, 778–808.

Zanutto E. L. Lu B. Hornik R. (2005). Using propensity score subclassification for multiple treatment doses to evaluate a national anti-drug media campaign. Journal of Educational and Behavioral Statistics, 30, 59–73.