**Date:** Tue, 29 Jan 2008 09:16:41 -0600
**Reply-To:** "Reutter, Alex" <areutter@spss.com>
**Sender:** "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
**From:** "Reutter, Alex" <areutter@spss.com>
**Subject:** Re: Conditional logistic problems
**In-Reply-To:** A<002701c861ea$4adf5150$2845cd80@ssw.buffalo.edu>
**Content-Type:** text/plain; charset="us-ascii"
Gene,

This doesn't directly help your problems with COXREG, but if the dataset is matched 1:1 and not 1:many, you can alternatively use Multinomial Logistic Regression (NOMREG). There's an example in Marija Norusis's Advanced Statistical Procedures Companion and another in the online help (Help>Case Studies, then Regression Models>Multinomial Logistic).

Cheers,
Alex

-----Original Message-----
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Gene Maguin
Sent: Monday, January 28, 2008 2:14 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Conditional logistic problems

All,

I have been working with another list subscriber who has a matched (1:1)
dataset and is trying to analyze relationships between variables using
conditional logistic regression (CLR). I have no experience with this type
of model. However, I did find a posting by Marta (shown below) as well as
several discussion sites. Since spss logistic won't do a conditinal
analysis, the trick is to use the coxreg procedure to do so. I believe I
have faithfully followed Marta's directions but am getting no results and
so, there is something I don't understand. Per Marta's posting, I have

COXREG ftime /STATUS=outcome(1) /STRATA=pair
/METHOD=ENTER x /PRINT=CI(95).

Where
Ftime is the survival time variable computed such that ftime=outcome+1.
outcome is the case-control variable with 0=control, 1=case.
Pair is the strata variable, 161 pairs.
X is the IV.

My case processing box shows

Case Processing Summary
N Percent
Cases available in analysis Event(a) 161 50.0%
Censored 0 .0%
Total 161 50.0%
Cases dropped Cases with missing values 0 .0%
Cases with negative time 0 .0%
Censored cases before the
earliest event in a stratum 161 50.0%
Total 322 100.0%
a Dependent Variable: ftime

Variables in the Equation(b)
Wald df Sig.
X . 0(a) .
aDegree of freedom reduced because of constant or linearly dependent
covariates
bConstant or Linearly Dependent Covariates
S = Stratum effect. x = .5093 + S;

If somebody can educate me about what I'm missing or need to look at, I'd
greatly appreciate it.

Thanks, Gene Maguin

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