Roger, thank you for the reference. I downloaded and checked out
-parmest-, but it doesn't give standardized regression coefficients as
an explicit option; however, the macro option would allow for
programming. Maybe my question is more basic, ie. do standardized
regression coefficients exist for proportional hazards models? If so,
what formula would be used to estimate them? I haven't found one yet.
There is a formula on p 75 of Long and Freese, Regression models for
categorical dependent variables using Stata, that uses quadratic forms
for dependent variables that may be conceptualized as latent variables,
eg. the logistic model, which leaves me with the question whether the
log-hazard of a Cox model may be considered as a latent variable? And
if so, two further questions 1) what residual to use (eg. Schoenfeld,
Martingale)? and 2) what is the variance of the residual (eg. probit
variance is fixed at 1)? Bill H.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Roger Newson
Sent: Wednesday, March 31, 2004 6:39 AM
To: [email protected]
Subject: Re: st: standardized regression coefficients for -stcox- ?
At 17:02 30/03/04 -0600, Bill Howells wrote:
>Are there any commands for obtaining standardized regression
>coefficients from -stcox- models, ie. analogous to -listcoef-? Or
maybe
>a way to restructure survival data into one of the models that work
with
>-listcoef-, eg. poisson, intreg, etc?
The -parmest- package (downloadable from SSC) might be a tool for the
job.
It creates a dataset with 1 obs per parameter of an estimated model
(created by any estimation command including -stcox-) and data on
estimates, confidence limits, standard errors, z-scores, p-values and
other
parameter attributes. In Stata, type
ssc desc parmest
to find out more.
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: [email protected]
Website: http://www.kcl-phs.org.uk/rogernewson
Opinions expressed are those of the author, not the institution.
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