(This article was first published on SAS and R, and kindly contributed to R-bloggers)
In examples 7.34 and 7.35 we described methods using propensity scores to account for possible confounding factors in an observational study.In addition to adjusting for the propensity score in a multiple regression and matching on the propensity score, researchers will often stratify by the propensity score, and carry out analyses within each group defined by these scores. With sufficient To leave a comment for the author, please follow the link and comment on his blog: SAS and R.
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Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).