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Covariate modelling question

From: Fiona Vanobberghen <fiona.vanobberghen>
Date: Thu, 26 Feb 2015 10:00:52 +0000

I posted this message a few days ago but it doesn't seem to have been
sent to the list - so I'm resending without the example output.
Best wishes

Dear all

I am attempting to do some covariate modelling, using the scm wizard in
Pirana. I have seen some results which I wasn't expecting and would be
grateful if anyone could shed any light on it for me.

Initially, I used a forward inclusion p value of 0.1 and a backward
elimination p value of 0.05. This resulted in quite a complex
(implausible) model (we do have a reasonably large dataset), and I
decided to be more stringent, using p<0.05 for inclusion (and the same
p>0.05 for elimination at the last step). As a shortcut, I could see
from the output from the first attempt (with p<0.1) what I expected the
final model to look like if I were to run it again with p<0.05, ie where
the process would truncate. Just to double check (and verify that
nothing would be eliminated at the last step), I re-ran the scm wizard
with the more stringent p<0.05. And the results are not what I
expected... Below I have pasted the output for the first few forward
steps from each attempt. The results are essentially the same up until
the third step, although we see some small differences in the OFV
creeping in from the second step. However, at the fourth step, the
results are completely different. This isn't what I was expecting, based
on my understanding of the model selection process. Is this a known
behaviour? Has anyone experienced this problem and/or know why these
differences might occur? I'd be grateful for any advice.

Many thanks in advance for your help.

Best wishes

*Fiona Vanobberghen (née Ewings), PhD*
Swiss Tropical and Public Health Institute
Socinstrasse 57, 4051, Basel, Switzerland
Tel: +41 61 284 87 41

Received on Thu Feb 26 2015 - 05:00:52 EST

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