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Re: st: estimating expenditure quartiles for subgroups of survey data

From   Steven Samuels <>
Subject   Re: st: estimating expenditure quartiles for subgroups of survey data
Date   Fri, 13 Jun 2008 10:36:00 -0400

I assume that you used -pctile- to compute your weighted quartiles.

I would not recommend hypothesis tests for percentiles of descriptive survey data with clustering and weights, even if I knew what tests to use (I don't). The distributions, including percentiles, of several finite populations will never be identical, and null hypotheses of equality are false a priori. (The exception is hypotheses about superpopulations.) Your question appears to be: how different are the expenditure distributions in the subpopulations? If so, I think that confidence intervals are a better approach. Download Roger Newson's -somsersd- package from SSC. It contains -cendif-, which will find confidence intervals for pairwise differences in percentiles and will accept probability weights and clusters.

Confining yourself to a small set of quantiles could mislead. If sample size permits, enlarge the set of percentiles that you feed to - pctile- and -cendif-. You might also check weighted histograms for multiple modes and other anomalies.


On Jun 12, 2008, at 4:09 PM, Waldo, Daniel R. (CMS/ORDI) wrote:

I would like to test for statistically significant differences in health
expenditure quartiles for subpopulations (different kinds of insurance)
of my survey data, but cannot seem to find the proper way to do this.
Can somebody point me in the right direction?

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