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3 votes
1 answer
248 views

Design-based standard errors in svyglm but w/o weights or stratification

For inverse probability weighting (IPW) in R the use of survey::svyglm is well established. I want to compare the results of 10K+ (!) models with and without the ...
jay.sf's user avatar
  • 878
3 votes
1 answer
2k views

Computing standard errors when using stratified sampling

I am trying to understand the following formula for the standard error of the population mean as estimated through stratified sampling. On the CRAN site, the formula given is $$ S_{\bar{x}_{\textit{...
ted's user avatar
  • 741
3 votes
1 answer
1k views

Why do R and SPSS give different SEs (complex survey with weights)?

My colleague and I are working with complex survey data (i.e., with weights). He is doing the analysis in SPSS, and I am trying to double-check his work, but I use R. We have a binary explanatory ...
Travis's user avatar
  • 33
1 vote
1 answer
87 views

How does the TraMiner Package Calculate Standard Error Using Weighted Data?

The TraMiner Package includes an option to include sampling weights in the analysis. However, I haven't found any discussion in the package documentation (or associated user manual) of how standard ...
LTD's user avatar
  • 11
0 votes
0 answers
279 views

Standard errors for population rates based on survey data

I have survey data that includes a random sample of emergency rooms in the United States. Each observation has a sampling weight that allows me to estimate the number of cases for a particular ...
justin's user avatar
  • 1