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Re: st: Unexpected proportions after survey commands
Jean-Gael,
First of all, you can use Stata's svy poststratification weights (as
opposed to probability weights) by creating a variable that has cell
totals for each poststratification cell. E.g,
TOURIND Community #
Yes 1 10
No 1 80
Yes 2 5
No 2 92
etc. You then use the -svyset- syntax for poststratification strata and
weights.
Alternatively, what you said about "true" vs. "sample" proportions
sounds fine, but you might not have done it correctly in practice. You
need to assign weights to both the tourism and non-tourism parts of the
sample. Also, you shouldn't use falsely high levels of precision--stick
with 2-4 digits.
Michael
Jean-Gael Collomb wrote:
Hello all,
I have a question about using post stratification weights and using
Stata's survey commands. After setting the weights, I do not get the
proportions I expected.
My overall research question is to see if tourism (TOURIND) influences
quality of life in several communities in a rural province of Namibia.
My aim was to conduct individual interviews in a sample of 10% of all
households in each community. I obtained household census counts from
key informants within the community and my own double checks during
field work. This random sample yielded a random sample of 395
interviews, of which only 9 (2.3%) were conducted with individuals
working in tourism. Given this very low number of respondents who
worked in tourism and my interest in trying to understand the impact
of tourism, I established a sampling frame restricted to individuals
working in tourism and interviewed 72 individuals. [Two of those
interviews were conducted with individuals not employed in tourism but
living in a household where someone was]. In total, I thus interviewed
467 people, among which 79 worked in tourism. My full sample
oversampled tourism employees and i think it would be wrong to derive
from it that 17% (79/467*100) of the population works in tourism. I
think Post stratification weights should be assigned to my data set to
correct for the oversampling. In fact, the percentage of the
population working in tourism varies by communities and thus different
weights should be calculated for different communities. I used
existing reports documenting total numbers of community residents
employed by local tourism operators and total population size as a
basis to calculate the "true" distribution of tourism employees
(weight2). The weights were calculated by dividing the “true”
percentage by the “oversampled” percentage.
The problem is that when I apply the weights in Stata, I do not get
the proportion I expected. Specifically, I expected that after svyset
_n [pweight = samplewt2] and svy: tab tourind, I would find that 0.84%
of the population could be labeled TOURIND, but Stata returns a value
of 3.25% (and similar discrepancies for each community).
I am not sure I am doing something wrong in calculating the weights,
assigning the weights to my dataset, or entering the tab commands in
svy mode. I’d greatly appreciate your help in helping move past this
and take advantage of survey commands in Stata.
Thank you very much if you have time to give me some feedback or point
me towards the best information source (textbook?).
Cheers,
Jean-Gael Collomb, [email protected]
(PS. I run Stata 10 in Mac OSX)
State code entered:
*ASSIGNING POST STRATIFICATION WEIGHTS
*-------------------------------------
gen samplewt2=0
label var samplewt2 "Post Stratification sample weight 2"
replace samplewt2=0.99975204562360500 if conservancy==1 & sample==1
replace samplewt2=0.04357333333333330 if conservancy==2 & sample==2
replace samplewt2=1.39197814207650000 if conservancy==2 & sample==1
replace samplewt2=0.10144078144078100 if conservancy==3 & sample==2
replace samplewt2=1.18320139407518000 if conservancy==3 & sample==1
replace samplewt2=0.05683908045977010 if conservancy==4 & sample==2
replace samplewt2=1.47985380116959000 if conservancy==4 & sample==1
replace samplewt2=0.01906976744186050 if conservancy==5 & sample==2
replace samplewt2=1.05030411449016000 if conservancy==5 & sample==1
tab tourind
bysort conservancy: tab tourind
*applying weight2 (those derived from IRDNC data)
svyset _n [pweight = samplewt2]
svy: tab tourind, percent
Jean-Gael "JG" Collomb
PhD candidate
School of Natural Resources and Environment / School of Forest
Resources and Conservation
University of Florida
[email protected]
[email protected]
+1 (352) 870 6696
*
* For searches and help try:
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--
Michael I. Lichter, Ph.D. <[email protected]>
Research Assistant Professor & NRSA Fellow
UB Department of Family Medicine / Primary Care Research Institute
UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
Office: CC 125 / Phone: 716-898-4751 / FAX: 716-898-3536
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/