[R] clogit and small sample sizes: what to do?

From: Johannes Elias <jelias_at_hygiene.uni-wuerzburg.de>
Date: Fri, 07 Nov 2008 16:54:35 +0100

Hash: SHA1

Conditional logistic regression and small sample sizes: what to do?

Dear R-Gurus,

[I run R 2.8.0 on WinXP. I have no formal training in statistics.]

Please feel free to skip the 'Blah blah part' for questions below.

Now clogit() (Package 'survival') produces some conflicting results:

Briefly, 10 of 11 cases have a certain exposure, compared to 9 of 33 controls. The odds ratio is significant (p-value = 0.000311) while the output of clogit() is inconclusive (.95 confidence intervals for risk factor range from 0 to infinity, conflicting 'likelihood ratio test' and 'Wald test') plus produces following warning message, "Warning message: In fitter(X, Y, strats, offset, init, control, weights = weights,: Ran out of iterations and did not converge." Tampering with the data (i.e. reducing the number of cases with the exposure to 7 of 11) renders the odds ratio unsignificant (p-value = 0.06681), yet makes clogit() assign a significant p-value to the exposure in question (0.043). Furthermore, the warning message is gone after the tampering.

Interestingly reducing (instead of increasing) cases with the risk factor yields a significant result with clogit().

I believe now, that this behaviour might be due to small sample size. Now I am looking for an R package to maybe circumvent this limitation of clogit(). (Alternatively, I could just chuck the project and order a Margerita. Maybe the risk factor is plainly not significant after all. But I digress...)

Six years ago, the following message was posted to this list:

   -----old post 2002------------
Dear R folks,
We completed a matched case-control study that was analyzed using conditional logistic regression. Because of the small sample size we need to calculate exact confidence intervals. The quick solution is to purchase LogExact by Cytel. However, we'd like to do this in R. Anyone have experience with this?

Many thanks,

Tomas Aragon, MD, DrPH

   -----old post 2002 end------------

At that time, the answers were not too encouraging. Anyway, I might have the very same query 2008.

Ok, I tried to do some homework and started to look for packages maybe implementing different methods. I did run across 'elrm' (Zamar, D., McNeney, B. & Graham, J., 2007), but I am unsure whether this package is appropriate for my original 1:3 matched design.

Thank you for your time and effort,


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