propensity score matching spss version 25

Examine the difference-in-means between Treated and Control for the outcome variable.In addition, before we implement a matching method, we’ll conduct the following analyses using the non-matched data: Examine covariate balance after matching.In this tutorial we’ll use nearest neighbor propensity score matching. Choose and execute a matching algorithm.Estimate the propensity score (the probability of being Treated given a set of pre-treatment covariates).To examine the effect of going to Catholic school (“Treated”) versus public school (“Control”) on student achievement using matching we will go through the following steps: To get the dataset used below (ecls.csv), please follow the instructions outlined here. UPDATE: Many people have asked for the data used in this tutorial. Because students who attend Catholic school on average are different from students who attend public school, we will use propensity score matching to get more credible causal estimates of Catholic schooling. In this tutorial we’ll analyze the effect of going to Catholic school, as opposed to public school, on student achievement. 4.3 Average absolute standardized difference.4 Examining covariate balance in the matched sample.2.1 Examining the region of common support.1.2 Difference-in-means: pre-treatment covariates.1.1 Difference-in-means: outcome variable.

Propensity score matching spss version 25