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


From   dwaldo1@umbc.edu
To   statalist@hsphsun2.harvard.edu
Subject   Re: Re: st: estimating expenditure quartiles for subgroups of survey dat
Date   Sat, 14 Jun 2008 07:08:09 -0400 (EDT)

Thanks, Steve, for some valuable suggestions.

Reflecting on this, it occurs to me that I could use gammafit to test the
location (and shape) parameters of the subpops' expenditures -- the gamma
appears to describe the distribution for people with expenditure -- and a
logit to test the probability of use.

I also dug back into the archives and came across a posting by Nick Cox
(distribution fitting curiosity, December 2006) that gets to the same end
by a different route.

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

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


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