Multilevel Regression and Post-stratification in Stata

Sometimes social scientists are interested in determining whether, and to what extent, the distribution of a given variable of interest Y varies across the categories of a second variable D. When the number of valid observations within one or more categories of D is small and/or collected data are affected by selection bias, relatively accurate estimates of E(Y|D) can be obtained by using a proper combination of multilevel regression modeling and poststratification, called the MrP approach (Gelman and Little 1997; Park, Gelman and Bafumi 2004; Lax and Phillips 2009). The purpose of this talk is to illustrate the main features and applications of -mrp-, a new user-written program that implements the MrP approach in Stata.