Hi All, I'm trying to run a conditional logistic regression in R (2.14.0) using clogit from the survival package. The dataset I have is relatively small (300 observations) with 25 matched strata- there are roughly 2 controls for each case, and some strata have multiple case/control groups. When I try to fit a very simple model with a binary outcome and a single continuous exposure R seems to freeze for a while, and 30 minutes later I receive the results. However, when I run the exact same conditional logistic regression model in STATA 10, the exact same answers are produced in <1 second. (Same coefficients, LR test resutls, standard errors, etc.). I just tried running an expanded model with covariates that I'd like to control for, but R has been unresponsive and I doubt it will resolve itself anytime soon. The syntax I'm using is:
library(survival) clogit(binary_out~contin_exp + strata(id), data=data) Various fixes I tried: 1) Upgrading from my prior install version of R 2.10.0 to 2.14.0, no resolution 2) Increased the memory size limit on R thinking that that might be the issue, but similar result I'm running a 32 bit windows machine, i5 CPU at 3.3 Ghz with 3.24 GB of ram. Any insights into what is occurring/how to increase the speed of this process would be greatly appreciated. Thanks in advance. Sincerely, Vincent [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.