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2012 Apr 15
0
correct standard errors (heteroskedasticity) using survey design
Hello all, I'm hoping someone can help clarify how the survey design method works in R. I currently have a data set that utilized a complex survey design. The only thing is that only the weight is provided. Thus, I constructed my survey design as: svdes<-svydesign(id=~1, weights=~weightvar, data=dataset) Then, I want to run an OLS model, so: fitsurv<-svyglm(y~x1+x2+x3...xk, design=svdes, data=dataset) But, I want to check if there is evidence of heteroskedasticity. If so, how would I correct the standard errors? Can the "sandwich" library do this? Are the standard err...
2012 Aug 10
1
Direct Method Age-Adjustment to Complex Survey Data
...e, rake, and simply multiplying the base weights by the correct proportions - nothing seems to hit the published numbers on the nose. I am trying to replicate any of the following: the stdize and stdweight parameters from a Stata complex survey analysis command (like this) svyset [w= WEIGHTVAR], psu(PSUVAR) strata(STRATAVAR) vce(linearized) svy: mean VARNAME, stdize(agecat) stdweight(agewt) the stdvar and stdwgt parameters from a SUDAAN proc descript call the ESTIMATE statement in a PROC SURVEYREG (used to generate adjusted means) in SAS version 9.2 I am attempting to...