On Thu, 31 May 2007, Strickland, Matthew (CDC/CCHP/NCBDDD) (CTR) wrote: > Dear R users, > > I have a large individual-level dataset (~700,000 records) which I am > performing a conditional logistic regression on. Key variables include > the dichotomous outcome, dichotomous exposure, and the stratum to which > each person belongs. > > Using this individual-level dataset I can successfully use clogit to > create the model I want. However reading this large .csv file into R and > running the models takes a fair amount of time. > > Alternatively, I could choose to "collapse" the dataset so that each row > has the number of events, number of individuals, and the exposure and > stratum. In SAS they call this the "events/trials" format. This would > make my dataset much smaller and presumably speed things up. >
I think you have described the data for forming a 2 by 2 by K table of counts. In which case, loglin(), loglm(), mantelhaen.test(), and - if K is not too large - glm(... , family=poisson) would be suitable. But you say 'models' above suggesting that there are some other variables. If so, you need to be a bit more specific in describing your setup. > So my question is: can I use clogit (or possibly another function) to > perform a conditional logistic regression when the data is in this > "events/trials" format? I am using R version 2.5.0. > > Thank you very much, > Matt Strickland > Birth Defects Branch > U.S. Centers for Disease Control > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > Charles C. Berry (858) 534-2098 Dept of Family/Preventive Medicine E mailto:[EMAIL PROTECTED] UC San Diego http://biostat.ucsd.edu/~cberry/ La Jolla, San Diego 92093-0901 ______________________________________________ R-help@stat.math.ethz.ch 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.