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

[Steven Samuels <sjhsamuels@earthlink.net>]

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.

-Steve



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?
> Thanks!
>
>
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