[R] Conditional logistic regression for "events/trials" format

[Charles C. Berry]

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
>
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>

Charles C. Berry                        (858) 534-2098
                                          Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	         UC San Diego
http://biostat.ucsd.edu/~cberry/         La Jolla, San Diego 92093-0901