inst/shiny/psa/references.md

References

Bryer, J.M., & Pruzek, R.M. (2011). An international comparison of private and public schools using multilevel propensity score methods and graphics (Abstract). Multivariate Behavior Research 46, 1011-1011

Dehejia, R. H., & Wahba, S. (1999). Causal e↵ects in nonexperimental studies: Reevaluating the evaluation of training programs. Journal of the American Statistical Association, 94(448), 1053–1062.

Diamond, A., & Sekhon, J.S. (2013). Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies. Review of Economics and Statistics. 95(3): 932--945.

Helmreich, J.E., & Pruzek, R.M. (2009). PSAgraphics: An R Package to Support Propensity Score Analysis. Journal of Statistical Software 29(6), 1-23. Retrieved from http://www.jstatsoft.org/v29/i06/.

Holland, P.W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945-960.

Pruzek, R. M., & Helmreich, J. E. (2009). Enhancing dependent sample analysis with graphics. Journal of Statistical Education, 17(1).

Pruzek, R.M., & Helmreich, J.E. (2011). Elemental Graphics for Analysis of Variance using the R Package granova. Retrieved from http://rmpruzek.com/wp-content/uploads/2011/07/ElementalGraphicsForANOVA.finalJune11.pdf

Rosenbaum, P. R. (2002). Observational studies (2nd ed.). New York, NY: Springer.

Rosenbaum, P. R. (2010). Design of observational studies. New York, NY: Springer.

Rosenbaum, P. R. (2012). Testing one hypothesis twice in observational studies. Biometrika, 99, 763-774.

Rosenbaum, P.R., & Rubin, D.B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

Sekhon, J. S. (2011). Multivariate and propensity score matching software with automated balance optimization: The matching package for r. Journal of Statistical Software, 42(7), 1–52. Retrieved from http://www.jstatsoft.org/v42/i07

Stuart, E. A. (2010). Matching methods for causal inference: A review and a look forward. Statistical Science, 25, 1-21.

Stuart, E. A., & Rubin, D. B. (2008). Best practices in quantitative methods. In J. Osborne (Ed.), (p. 155-176). Sage Publications.



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