|Date: ||Wed, 10 Dec 2008 16:25:54 -0500|
|Reply-To: ||"Whanger, J. Mr. CTR" <James.Whanger@med.navy.mil>|
|Sender: ||"SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>|
|From: ||"Whanger, J. Mr. CTR" <James.Whanger@med.navy.mil>|
|Subject: ||Re: validating a logistic regression model|
|Content-Type: ||text/plain; charset="iso-8859-1"|
Before proceeding, you may want to consider the logic underlying the notion of cross-validation. If the goal is to most accurately estimate population parameters that can later be used for probabilistic prediction, then a large sample that is representative of the population is the solution rather than reducing statistical power via sample splitting or bootstrapping. When the sample size is large enough, bootstrapped parameter estimates will be roughly equivalent to non-bootstrapped.
However, because sample splitting cross-validation & bootstrapping are considered "best practice" you will likely need to be prepared to defend why a larger sample size provides the better estimate of population parameters relative to the other two methods.
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of J P
Sent: Wednesday, December 10, 2008 3:33 PM
Subject: validating a logistic regression model
I am attempting to learn how to valide a logististic regression model. I've been reading about bootstrapping and cross validation, etc. But have found no instruction on how to actually conduct the anaysis and interpret the results. Any references on this subject or advice on how to perform this with SPSS is greatly appreciated.
Here is an example of what I am talking about....http://symptomresearch.nih.gov/chapter_8/sec7/cess7pg14.htm
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