Dear Statalist,
Per Nick's message (st: "Thanks in advance" and closure of threads), let
me wrap up my thread and say that Jeff Pitblado and Michael Blasnik
along with Emma Slaymaker were so kind to reply to me and my original
problem is well-solved with these programs. As a new programmer, it is
incredibly helpful to get this kind of help and it pushes me much
further on the path to programming these kinds of complicated programs
myself, so I thank you for your goodwill towards me and patience as I
try to learn.
Claire Kamp Dush
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Jeff
Pitblado, StataCorp LP
Sent: Thursday, July 19, 2007 11:32 AM
To: [email protected]
Subject: Re: st: svy: mean and descriptive tables
Claire Kamp Dush <[email protected]> wants to produce a table of
means
and standard deviations from variables in a survey dataset:
> I am running several svy: mean commands for a descriptive statistic
> table I am creating. Here is the code I am running:
>
> After svy setting the variables
>
> foreach var of varlist var1 var2 var3 {
> svy: mean `var'
> di sqrt(e(N) * el(e(V_srs), 1, 1))
> }
>
> I am using Stata 9. This code is working fine, and the first line
> calculates the weighted mean and the second the standard deviation.
My
> question is:
> Is there a way for me to write a code to create a table for my means
and
> standard deviations automatically? For instance, I would like a table
> as follows:
>
> Var 1 mean1 sd1
> Var 2 mean2 sd2
> Var 3 mean3 sd3
>
>
> Any suggestions on how I could do this? Here is my first attempt at a
> program:
>
> prog svymean
> local mean = svy: mean `1'
> local sd = di sqrt(e(N) * el(e(V_srs), 1, 1))
> display e(varlist) `mean' `sd'
> end
>
> Then I thought I would run this for each of my variables and copy and
> paste the results into a text file and then convert into an excel or
> word file. But, this didn't work because it wouldn't calculate the
svy:
> mean of `1'.
>
> I searched Statalist and I did not see a ready solution, but I could
> have missed something.
>
> In advance, I never know whether to e-mail thank yous and fill up
> everyone's in boxes that much more, so in advance, a whole-hearted
thank
> you to anyone who replies. I really appreciate it.
In Stata 10 there is a new -estat sd- command that does this, see the
section
of this email titled 'Stata 10 Users' for an example.
Here is a rewrite of Claire's program that works.
prog mysvymean
quietly svy: mean `1'
local sd = sqrt(e(N) * el(e(V_srs), 1, 1))
display e(varlist) " " _b[`1'] " " `sd'
end
------------------------------------------------------------------------
-----
Stata 9 Users
There are two ways I can think of building a table from the results of
the
-svy: mean- command.
1. Let -svy: mean- perform the estimation all at once, then pick the
pieces
I want from -e(b)- (via _b[...]) and -e(V_srs)-. This will restrict
the
estimation sample to the set of observations that contain no missing
values in the variables of interest.
2. Collect the information from -svy: mean- by looping over the
variables.
This will allow the full set of observations to be used for
computing the
mean and sd for each varaible.
I wrote a program for each case and named them -mean_sd_table1- and
-mean_sd_table2-, corresponding to the above two descriptions.
***** BEGIN:
program mean_sd_table1
syntax varlist
tempname v
quietly svy: mean `varlist'
matrix `v' = e(N)*vecdiag(e(V_srs))
local k : list sizeof varlist
display as txt %12s "Variable" ///
as txt %10s "Mean" ///
as txt %12s "Std. Dev."
forval i = 1/`k' {
local var : word `i' of `varlist'
display as txt %12s "`var'" ///
" " as res %9.0g _b[`var'] ///
" " as res %9.0g sqrt(`v'[1,`i'])
}
end
program mean_sd_table2
syntax varlist
tempname sd
local k : list sizeof varlist
display as txt %12s "Variable" ///
as txt %10s "N" ///
as txt %12s "Mean" ///
as txt %12s "Std. Dev."
forval i = 1/`k' {
local var : word `i' of `varlist'
quietly svy: mean `var'
scalar `sd' = sqrt(e(N)*el(e(V_srs),1,1))
display as txt %12s "`var'" ///
" " as res %9.0g e(N) ///
" " as res %9.0g _b[`var'] ///
" " as res %9.0g `sd'
}
end
***** END:
Here are some example results
***** BEGIN:
. webuse nhanes2
. svyset psu [pw=finalwgt], strata(strata)
pweight: finalwgt
VCE: linearized
Single unit: missing
Strata 1: strata
SU 1: psu
FPC 1: <zero>
. mean_sd_table1 smsa height weight bpsystol bpdiast tcresult tgresult
Variable Mean Std. Dev.
smsa 2.50289 1.235087
height 168.6915 9.613919
weight 72.05973 15.50079
bpsystol 126.1283 21.16074
bpdiast 80.38098 12.92431
tcresult 211.3975 47.08961
tgresult 138.576 95.90575
. mean_sd_table2 smsa height weight bpsystol bpdiast tcresult tgresult
Variable N Mean Std. Dev.
smsa 10351 2.496329 1.239231
height 10351 168.4599 9.699111
weight 10351 71.90064 15.43281
bpsystol 10351 126.9458 21.40073
bpdiast 10351 81.01726 12.79357
tcresult 10351 213.0977 48.45305
tgresult 5050 138.576 95.90575
***** END:
Note that I include a column for the sample size in -mean_sd_table2- to
show
that the estimation sample can differ between variables.
------------------------------------------------------------------------
-----
Stata 10 Users
There is the new -estat sd- command allowed after -svy: mean- that
produces
a table similar to the one produced by -mean_sd_table2-. So a mean/std.
dev.
table could be produced using something like the following example
. webuse nhanes2
. svyset psu [pw=finalwgt], strata(strata)
. svy: mean smsa height weight bpsystol bpdiast tcresult
tgresult
. estat sd
The table resulting from -estat sd- is
-------------------------------------
| Mean Std. Dev.
-------------+-----------------------
smsa | 2.50289 1.235087
height | 168.6915 9.613919
weight | 72.05973 15.50079
bpsystol | 126.1283 21.16074
bpdiast | 80.38098 12.92431
tcresult | 211.3975 47.08961
tgresult | 138.576 95.90575
-------------------------------------
Note that -estat sd- also handles results that employed the -subpop()-
option
of -svy- and the -over()- option of -mean-.
--Jeff
[email protected]
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