Dear list, I am trying to set up a propensity-weighted regression using the survey package. Most of my population is sampled with a sampling probability of one (that is, I have the full population). However, for a subset of the data I have only a 50% sample of the full population. In previous work on the data, I analyzed these data using SAS and STATA. In those packages I used a propensity weight of 1/[sampling probability] in various generalized linear regression-procedures, but I am having trouble setting this up. I bet the solution is simple, but I’m a R newbie. Code to illustrate my problem below.
Thanks Laust # loading survey library(survey) # creating data listc <- c("Denmark","Finland","Norway","Sweden","Denmark","Finland","Norway","Sweden") listw <- c(1,2,1,1,1,1,1,1) listd <- c(0,0,0,0,1000,1000,1000,2000) listt <- c(750000,500000,900000,1900000,5000,5000,5000,10000) list.cwdt <- c(listc, listw, listd, listt) country <- data.frame(country=listc,weight=listw,deaths=listd,yrs_at_risk=listt) # running a frequency weighted regression to get the correct point estimates for comparison glm <- glm(deaths ~ country + offset(log(yrs_at_risk)), weights=weight, data=country, family=poisson()) summary(glm) regTermTest(glm, ~ country) # running survey weighted regression svy <- svydesign(~0,,data=country, weight=~weight) svyglm <- svyglm(deaths ~ country + offset(log(yrs_at_risk)), design=svy, data=country, family=poisson()) summary(svyglm) # point estimates are correct, but standard error is way too large regTermTest(svyglm, ~ country) # test indicates no country differences ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.