I am trying to perform a conditional univariate regression in a matched case control group.

The raw data look like this (matset=match set, case=diseased patients, retr=an exposure); cases are matched with controls 1:3:

> m

matset case retr

1 1 1 0

2 1 0 1

3 1 0 0

4 1 0 1

5 2 1 0

6 2 0 0

7 2 0 0

8 2 0 0

9 3 1 1

10 3 0 0

11 3 0 0

12 3 0 0

13 4 1 1

14 4 0 0

15 4 0 1

16 4 0 0

17 5 1 1

18 5 0 0

19 5 0 0

20 5 0 0

21 6 1 1

22 6 0 0

23 6 0 0

24 6 0 0

25 7 1 0

26 7 0 1

27 7 0 0

28 7 0 0

29 8 1 1

30 8 0 0

31 8 0 1

32 8 0 1

33 9 1 1

34 9 0 1

35 9 0 0

36 9 0 1

37 10 1 1

38 10 0 0

39 10 0 0

40 10 0 1

41 11 1 0

42 11 0 0

43 11 0 0

44 11 0 0

Calling the appropriate function works like a dream:

> clogit(case~retr+strata(matset))

Call:

clogit(case ~ retr + strata(matset))

coef exp(coef) se(coef) z p

retr 1.70 5.45 0.84 2.02 0.043

Likelihood ratio test=4.86 on 1 df, p=0.0275 n= 44

I have just one tiny problem. The above data are fake! In the real data I have three cases more with the exposure "retr", which means (at least to me) that I have an even stronger case for assuming that there´s an association between the exposure "retr" and case. Unfortunately, however, conditional logistic regression does not work with the real data. Calling the above function with the authentic data yields the following result:

> cl <- clogit(case~retr+strata(matset))

Warning message:

In fitter(X, Y, strats, offset, init, control, weights = weights, :

Ran out of iterations and did not converge

and more: ....

> summary(cl)

Call:

coxph(formula = Surv(rep(1, 44L), case) ~ retr + strata(matset),

method = "exact")

n= 44

coef exp(coef) se(coef) z p

retr 21.8 2.99e+09 13666 0.00160 1

exp(coef) exp(-coef) lower .95 upper .95

retr 2.99e+09 3.35e-10 0 Inf

Rsquare= 0.32 (max possible= 0.5 )

Likelihood ratio test= 17.0 on 1 df, p=3.79e-05

Wald test = 0 on 1 df, p=0.999

Score (logrank) test = 13.4 on 1 df, p=0.000257

Nice. The lower .95 confidence interval has become 0. There goes this association. My boss will be delighted! How can this be?

I appreciate any helpful comment.

Greetings, Pisti