Censoring is not the only reason for preferring survival analysis to OLS
regression for event times or logged event times. As is pointed out in
Cleves, Gould and Gutierrez, AN INTRODUCTION TO SURVIVAL ANALYSIS USING
STATA, censorship could be handled through selection models. It is
rather that the distribution of event times are often far from normal
that makes survival models usually superior to OLS regression. David
Greenberg, Sociology Department, New York University.
----- Original Message -----
From: Ronan Conroy <[email protected]>
Date: Wednesday, June 12, 2002 10:10 am
Subject: Re: st: OLS regression versus survival analysis
> on 12/6/02 1:05 PM, ellen mastenbroek at [email protected]
> wrote:
> > I have set out to do a survival analysis, but it has become
> clear that only 3
> > % of the cases are censored. Is it advisable to then carry out
> regular OLS
> > regression instead (the advantage being that OLS results are
> more easy to
> > interpret)?
>
> No. Your endpoint is binary. You want to figure out what effect
> does a
> particular predictor have on the risk of an event happening.
> That's a hazard
> ratio.
>
> Start with Kaplan Meier graphs, which are even easier to interpret
> than OLS
> regression, and work from there.
>
>
>
> Ronan M Conroy ([email protected])
> Lecturer in Biostatistics
> Royal College of Surgeons
> Dublin 2, Ireland
> +353 1 402 2431 (fax 2329)
>
> --------------------
> And now, Mr President, how about the global alliance against
> climate change?
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