Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: Re: parmby & Beta


From   Fred Wolfe <fwolfe@arthritis-research.org>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: parmby & Beta
Date   Tue, 15 Jul 2003 10:03:44 -0500

Thanks, Roger.

Still on parmest and parmby, it might be helpful to be able to list with clist rather than list in order to get rid of Stata's lines.

Fred

At 03:55 PM 7/15/2003 +0100, you wrote:

At 09:17 15/07/03 -0500, Fred Wolfe wrote:
Is there anyway to get -parmby- output to include beta (Beta), as in:

parmby "reg cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration, beta", saving(testme, replace) for(estimate min95 max95 %8.2f p %8.1e) li(*)
This is not a simple thing to do, because -regress- does not save any such estimation result as -e(Beta)-. However, you could always standardise your Y- and X-variables before doing your regression, as in the following program:

foreach X of var cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration {
summ `X'
replace `X'=(`X'-r(mean))/r(sd)
}
parmby "reg cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration, beta", saving(testme, replace) for(estimate min95 max95 %8.2f p %8.1e) li(*)

This would code all your Y- and X-variables to a scale of SDs from the mean, causing -estimate-, -min95- and -max95- to be expressed in Y-axis SDs per X-axis SD. To eliminate missing values listwise, you might type instead:

gene byte listmiss=0
foreach X of var cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration {
replace listmiss=1 if missing(`X')
}
foreach X of var cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration {
replace `X'=. if listmiss
summ `X'
replace `X'=(`X'-r(mean))/r(sd)
}
parmby "reg cutdown high pain_ haq_ depress glb age sex edlevel white inctouse duration, beta", saving(testme, replace) for(estimate min95 max95 %8.2f p %8.1e) li(*)

This would recode all your X- and Y-variables to missing in observations where any of the variables were previously missing, or to a scale of SDs from the mean otherwise, where the SDs and means are from observations not deleted listwise.

I hope this helps.

Roger


--
Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648
Fax: 020 7848 6620 International +44 20 7848 6620
or 020 7848 6605 International +44 20 7848 6605
Email: roger.newson@kcl.ac.uk
Website: http://www.kcl-phs.org.uk/rogernewson

Opinions expressed are those of the author, not the institution.

*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/

Fred Wolfe
National Data Bank for Rheumatic Diseases
Wichita, Kansas
Tel (316) 263-2125     Fax (316) 263-0761
fwolfe@arthritis-research.org


*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index