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 <[email protected]>
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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