
From  Steven Samuels <ssamuels@albany.edu> 
To  statalist@hsphsun2.harvard.edu 
Subject  Re: st: Weights in survey design 
Date  Sun, 18 Mar 2007 22:27:57 0400 
I have a large dataset with weights calculated as PPS based on household
size, stratified by sex. The age group respondents are from 1664.
I am interested in looking at data only from those aged 1624. I can
use the subpop command "subpop(if age>=16 & age<=24)" for all the
commands. But I am wondering if I can drop all other cases (keep if
age>=16 & age<=24) and the 'reset' my weights based only on those aged
1624.
In the original form (with all data) I have the following summary data:
(note the survey design is quiet a simple one)
Svyset
pweight: pps
VCE: linearized
Strata 1: sex
SU 1: <observations>
FPC 1: <zero>
. svy: tab sex
(running tabulate on estimation sample)
Number of strata = 2 Number of obs = 8664
Number of PSUs = 8664 Population size = 8664
Design df = 8662

sex  proportions
+
female  .5046
male  .4954

Total  1

Key: proportions = cell proportions
If I select the subgroup (age 1624):
. svy,subpop(if age<=24): tab sex
(running tabulate on estimation sample)
Number of strata = 2 Number of obs = 8664
Number of PSUs = 8664 Population size = 8664
Subpop. no. of obs = 999
Subpop. size = 1438.7586
Design df = 8662

sex  proportions
+
female  .4599
male  .5401

Total  1

Key: proportions = cell proportions
When I reset my weights with data only representing those 1624 years of
age (ie., as if this was the way I original designed my study) I get the
following results:
. svy: tab sex
(running tabulate on estimation sample)
Number of strata = 2 Number of obs = 999
Number of PSUs = 999 Population size = 999
Design df = 997

sex  proportions
+
female  .4655
male  .5345

Total  1

Key: proportions = cell proportions
As it can be seen there is now a difference in the proportions between
using subpop and resetting my weights. Is this a problem?
Jason
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