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st: Jackknife standard e​rrors using replicat​e weights in Stata 1​2.1​


From   Annelies Blom <blom@survex.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: Jackknife standard e​rrors using replicat​e weights in Stata 1​2.1​
Date   Tue, 19 Feb 2013 16:36:27 +0100 (CET)

Dear colleagues,

for some analyses that I am currently conducting I have a dataset with a complex
sample design with replicate weights. The replicate weights were produced with a
jackknife(1) procedure. Various analyses are to be conducted with this setup.
Other project partners conduct the analyses in WesVar and our results have to be
comparable to theirs. I  prefer using Stata, but am encoutering problems.

An example of my svyset and analysis command:
svyset [pw = weight0], jkrw(weight1 - weight80, multiplier(1))
svy jackknife: proportion age

The following setup and command yields the same results:
svyset [pw = weight0], jkrw(weight1 - weight80, multiplier(1)) vce(jackknife)
svy: proportion age

The problem:
The standard errors calculated by Stata with these commands are unplausibly
small. In addition, for some variables Stata does not give any SEs at all (or no
confidence intervalls). The SEs when not specifying jackknife SEs (i.e. when
calculating Taylor linearized SEs, which is the default) are much more
plausible. And they are complete.

Via the Stata search function I found
<http://www.ats.ucla.edu/stat/stata/library/replicate_weights.htm>
These researchers state that "although the command will run (and run faster)
without the jackknife option after the svy, you will get linearized standard
errors instead of the jackknife standard error.  This jackknife standard error
matches the standard errors produced by both SUDAAN and WesVar."
They refer to Stata 9, while I am working in Stata 12.1. According to them, if I
do not specify jackknife SEs, my results are not be comparable to the WesVar
results.

My questions:
- Are the jackknife SEs calculated by Stata 12.1 correct? If so, why do I get
missing SEs?
- How can I solve these problems while at the same time remaining comparable
with analyses conducted in WesVar?

With best wishes,
Annelies

---
Annelies Blom, Ph.D.
Survex - Survey Methods Consulting
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