Posted by
Hector Maletta on
Aug 23, 2006; 6:59pm
URL: http://spssx-discussion.165.s1.nabble.com/Re-interpretation-of-the-warning-message-tp1070503p1070504.html
Lana,
Sorry my guess didn't work. I'm afraid that was my one bright idea for
today. Even sorrier not to have another one for the moment...
The Yes-No and No-Yes cells in your table (copied below) have fewer cases
than the Yes-Yes and No-No cells, but they are still in the hundreds, so I
do not think lack of cases is the problem. Marta Garcia-Granero, the
resident Math Stat genius in this list, also suspected zero cells and small
number of cases in some cells, but that's not the case I'm afraid. Neither
are the two variables unrelated, as shown by the highly significant chi
square you found. There are more things in Cox Regression, apparently, than
our philosophy can dream, to paraphrase Hamlet.
Back to square one, for the time being. The non convergence message you
received is yet to be explained.
May perhaps the hazards be non proportional? Perhaps they are so strongly
non proportional that the whole procedure fails to converge? You may do a
Kaplan-Meier of reentry times for children discharged due to reunification
and another for children discharged due to other reasons, and see whether
the reentry curves are parallel, or you may run Cox again with cause of
discharge as a binary covariate as before but also with a time varying
covariate, like time itself to keep it simple (If that fails try with log
time or time squared, just in case). You may also run Cox with just the
time-varying covariate, stratified by the cause of discharge, and inspect
the curves for hazard proportionality.
Hector
-----Mensaje original-----
From: Yampolskaya, Svetlana [mailto:
[hidden email]]
Date: Wednesday, August 23, 2006 1:29 PM
To: Hector Maletta
Subject: RE: interpretation of the warning message
Hector,
I did the table. Please see attached. Pearson Chi-Square = 26107.16.
There are 2594 yes-yes cases... Any ideas?
Crosstabulation
Count
REENTRY Total
No Yes
REUNIFICATION No 31508 428 31936
Yes 300 2594 2894
Total 31808 3022 34830
Lana
-----Original Message-----
From: Hector Maletta [mailto:
[hidden email]]
Sent: Wednesday, August 23, 2006 11:07 AM
To: Yampolskaya, Svetlana
Subject: RE: interpretation of the warning message
I am puzzled too. That makes two of us, Lana. Just to speculate about
it I may offer this (speculating is free): the % of the event is about
9%, and even less than that would have reunification as a reason for
discharge, so perhaps having few cases involved is not really to discard
out of hand, especially if the relationship between the two is not
strong. Try a 2x2 table of reunification as a reason (Yes/No) and
reentry in foster care within 12 months (Yes/No) and check the degree of
association and the number of Yes-Yes cases. If the association is weak,
and there are relatively few Yes-Yes cases, we may be into something. I
don't bet much on it, but it is a possibility.
Hector
-----Mensaje original-----
De: Yampolskaya, Svetlana [mailto:
[hidden email]] Enviado el:
Wednesday, August 23, 2006 11:45 AM
Para: Hector Maletta
Asunto: RE: interpretation of the warning message
Hector,
Thank you for your reply but I am still puzzled because I have 34,830
cases of children who exited foster care during two years. 3,022
reentered foster care within 12 months. So I am trying to look at time
to reentry. In this model I used only one covariate - reunification as a
reason for discharge. I coded that variable 1 - reunification as a
reason for discharge and 0 - other reasons. When I do the same analysis
and use a different covariate - placement with relatives as a reason for
discharge - the model runs without any problem. Multivariate model runs
without problems too.
Any advise will be greatly appreciated,
Lana
-----Original Message-----
From: Hector Maletta [mailto:
[hidden email]]
Sent: Wednesday, August 23, 2006 10:32 AM
To: Yampolskaya, Svetlana;
[hidden email]
Subject: RE: interpretation of the warning message
You probably were doing it stepwise, and the procedure failed to
converge at some step, so it judged it wise to stop at that step and not
trying to introduce further variables. Or perhaps you were doing it in a
single step, and the model simply did not converge. It just happens
sometimes, when the data fail to fit the model.
The reasons may vary. Increasing the number of iterations seldom helps.
Relaxing the convergence criterion is close to cheating and seldom
advisable. Also, it seldom works either (the failure to converge is
often by a much wider margin than any reasonable relaxation you may
introduce in the convergence criterion). Perhaps you have too few cases
to arrive at a significant solution, or perhaps the model is poorly
specified. Perhaps the hazards are not proportional, so Cox does not
apply unless some time-related covariates are introduced. Try to modify
the model, e.g. introducing time-varying covariates, or changing the
list of covariates by withdrawing some of them that seem to have less
strong relationship with the event of interest. Perhaps you may try some
simpler models first, to see whether the covariates fit the data
(predict survival) one by one, or in pairs, before running a more
complicated model. Sorry to say I do not have a magic bullet, but this,
as poetry, is more perspiration than inspiration.
Hector
-----Mensaje original-----
De: SPSSX(r) Discussion [mailto:
[hidden email]] En nombre de
Yampolskaya, Svetlana Enviado el: Wednesday, August 23, 2006 11:20 AM
Para:
[hidden email]
Asunto: Re: interpretation of the warning message
Dear List,
I am trying to do Cox regression (bivariate analysis) and I have this
message that I cannot interpret.
Can you please help and tell me what was wrong?
Warnings
Since coefficients did not converge, no further models will be fitted.
Thank you,
Lana