You might try something like the following. I use it to output a table
comprising results from several t-tests. (Use -return list- to identify
the which factors are available for use after your regression.)
tempname out
postfile `out' <output variable names here> using outfile, replace
foreach var of varlist <variables to be analyzed {
qui ttest `var', by(case)
post `out' ("`var'") (r(mu_2)) (r(sd_2)) (r(N_2)) (r(mu_1)) (r(sd_1))
/*
*/ (r(N_1)) (r(p))
}
postclose `out'
use outfile, clear
qui {
for var case sd1 control sd2: format X %6.2f
format p %4.3f
}
list, clean noobs
*At this point, I just copy the output to a Word document.
Hope this helps,
-pv
______________________________
Paul F. Visintainer, PhD
Professor and Program Director
Health Quantitative Sciences
School of Public Health
New York Medical College
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Garrard,
Wendy M.
Sent: Tuesday, November 23, 2004 4:12 PM
To: [email protected]
Subject: st: Extracting B coefs and p's from "foreach" regression
Hi All,
As part of preliminary descriptive analysis I need to examine pairwise
correlations between the effect size and a large number of possible
covariates. The tricky part is that I have discovered I need to examine
pairwise correlations which take into account a random effects
component. I can do this by specifying bivariate random effect
regressions using a metaregW macro in a foreach command as below:
*****
foreach var of varlist VarGrp1_* VarGrp_2* VarGrp_3* {
metaregW EffectSize `var' [aw=weight] , model(ml)
}
*****
But, this produces lots of extraneous output (R^2, Qs, 95%CIs, etc.)
since I only need the B1_coef and p-value from each run.
So, I am looking for a way to either capture the target values in a
table/list via a modification of the above command, or an alternative
method of creating a list of the B1_coefs and p's for this problem.
Any suggestions?
Much thanks,
Wendy
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