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Re: st: ROC with complex data sets
Sharonda:
Short answer to your question:
Round the pweight variable to the nearest integer and use the
resulting variable as an "fweight".
Long answer: The ROC programs will not take into account other
aspects of the survey (stratification, clustering, multiple stages).
Therefore confidence intervals and p-values quoted in the output will
be wrong. Also, the ROC analysis will not be much good if your
model is not good: so you are still obligated to build a good model
and check its fit. For example, if there are strong interactions, you
should include them in your model. Use Stata's survey features: -
svyset- your data and build your model with Stata's -svy- logistic
command. You may also want to learn about Stata's -zinb- command,
which can demonstrate failure of the ordinary logistic model.
Read the survey documentation to understand how the weighting was
done. If any part of the weighting or stratification involved your
outcome variable, you should probably run an unweighted analysis.
-Steven
On Aug 20, 2007, at 8:34 AM, Taylor, Sharonda A. wrote:
I am very new to research. I am attempting to do ROC analysis using
a complex survey that uses pweights. Stata 9.2 uses frequency
weights. I understand that pweights and fweights are not
interchangeable. Are there any downloads that will allow me to run
the analysis with the pweights? Please advise.
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