Re: Binary logistic regression - poor models

Posted by Rich Ulrich on Apr 26, 2016; 3:31pm
URL: http://spssx-discussion.165.s1.nabble.com/Binary-logistic-regression-poor-models-tp5732023p5732041.html

Agnes,
Basically, "no".  The rule of thumb is applied to the overall count, so
you should be okay there.

On the other hand, if you have any unusual distributions (say, some drug
that shows up only 10 times in all), then you should always remain aware
that Maximum Likelihood solutions sometimes do not like 0's.  (So, if something
goes obviously wrong, such variables might be dropped to see if that fixes the
problem -- I might try that even before looking at the cell counts, if I had not
looked at all the two-way tabulations at the start, just to make sure that my
dataset had no grossly apparent errors.)

--
Rich Ulrich

> Date: Tue, 26 Apr 2016 07:26:38 -0700

> From: [hidden email]
> Subject: Re: Binary logistic regression - poor models
> To: [hidden email]
>
> I don't have time to respond to this right now, but am replying so that
> Agnes' message below gets distributed to the mailing list. (Nabble shows
> that none of her messages have actually been posted to the mailing list.)
> Perhaps Rich or someone else will have time to jump in before I do.
>
>
> dfva wrote
> > Hi HTH!
> >
> > I have 25 065 samples (patients), and in these samples I have about 2300
> > patients with heart failure.
> > I thought it must have been big enough sample set.
> >
> > Should I check for each variable that in each stratum there are minimum 15
> > patients with heart failure?
> > I mean e.g:
> > - check that among patients having diabetes mellitus is minimum 15
> > patients with heart failure - and in the same way for other diseases?
> > - and check for each drug, that among patients were administered for this
> > drug are also minimum 15 patients with heart failure - and in the same way
> > for all drugs?
> >
> >
> > Thank you:
> > Agnes
>
>
>
>
>
> -----
> --
> Bruce Weaver
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