Re: interpretation of the warning message

Posted by Marta García-Granero on Aug 23, 2006; 4:04pm
URL: http://spssx-discussion.165.s1.nabble.com/Re-interpretation-of-the-warning-message-tp1070503p1070508.html

Hi Hector&Lana

Whenever I got a message like the one Lana reports (in logistic or Cox
regression), it was a problem of small number of cases/events combined
with too many qualitative predictors. This caused an elevated number
of patterns (combination of every level of every predictor) and some
cells had 0 cases/events. I even remember a memorable case where a 3
binary predictors model had been fitted with a total sample size of 36
subjects, with only 10 events (and, yes, it was stepwise - ouch! -,
and I daren't mention the total number of predictors involved in the
process that the authors tested). The statistical analysis was done
with a very old version of SPSS (PC+, before Windows era), that gave
the same warning Lana reports, but also gave a model (with OR of
around 5,000,000 for every predictor - fortunately, new versions of
SPSS just quit fitting the model). Those boars (no typo error here,
I'm insulting them) insisted in publishing the results, against my
opinion (at least, I got my name OUT of that hideous paper, I shudder
when I imagine getting thanked for my statistical assistance in that
horrible contraption).

I would not complicate the model, but simplify it. Run a CROSSTABS of
events against predictors, and check if for some predictor the number
of events in one cell at least is low. Recode your qualitative
predictors to a lower number of categories (if possible), or consider
not including those qualitative predictors with low variability (a
single value has a frequency of 90% or more, while the rest of the
values are poorly represented).

HTH,
Marta

Hector wrote:

HM> You probably were doing it stepwise, and the procedure failed to converge at
HM> some step, so it judged it wise to stop at that step and not trying to
HM> introduce further variables. Or perhaps you were doing it in a single step,
HM> and the model simply did not converge. It just happens sometimes, when the
HM> data fail to fit the model.
HM> The reasons may vary. Increasing the number of iterations seldom helps.
HM> Relaxing the convergence criterion is close to cheating and seldom
HM> advisable. Also, it seldom works either (the failure to converge is often by
HM> a much wider margin than any reasonable relaxation you may introduce in the
HM> convergence criterion). Perhaps you have too few cases to arrive at a
HM> significant solution, or perhaps the model is poorly specified. Perhaps the
HM> hazards are not proportional, so Cox does not apply unless some time-related
HM> covariates are introduced. Try to modify the model, e.g. introducing
HM> time-varying covariates, or changing the list of covariates by withdrawing
HM> some of them that seem to have less strong relationship with the event of
HM> interest. Perhaps you may try some simpler models first, to see whether the
HM> covariates fit the data (predict survival) one by one, or in pairs, before
HM> running a more complicated model. Sorry to say I do not have a magic bullet,
HM> but this, as poetry, is more perspiration than inspiration.

Lana wrote:

HM> I am trying to do Cox regression (bivariate analysis) and I have this
HM> message that I cannot interpret.

HM> Can you please help and tell me what was wrong?

HM> Warnings
HM> Since coefficients did not converge, no further models will be fitted.


---
"It is unwise to use a statistical procedure whose use one does
not understand. SPSS syntax guide cannot supply this knowledge, and it
is certainly no substitute for the basic understanding of statistics
and statistical thinking that is essential for the wise choice of
methods and the correct interpretation of their results".

(Adapted from WinPepi manual - I'm sure Joe Abrahmson will not mind)