I would say that if the OP even contemplated this, it strongly suggests that she needs to consult a local statistician for help.
Cheers, Bert On Wed, Nov 27, 2013 at 1:14 PM, Ben Bolker <bbol...@gmail.com> wrote: > Erika Barthelmess <barthelmess <at> stlawu.edu> writes: > >> Hi everyone, >> >> I'm new to this list and have searched R help prior for an answer >> to this question, without luck. If I'm >> posting in error, please forgive. >> >> I'm thinking about using package MuMIn to do multimodel inference >> with logistic regression. I have many >> (25) possible predictors and am curious if there is a way to >> estimate how long the dredge command might take >> to run? >> >> Any suggestions most welcome. >> >> Thanks, >> erika > > This is likely to be a bad idea. With 25 predictors you have 2^25 = > 33 million candidate models (you can think of an array of models, each > predictor is either present or absent in each model -- that makes this > a set of 25-digit binary strings ...). (If this doesn't make sense, > convince yourself by writing out the number of possible models for a > 1-parameter (2), 2-parameter (4), and 3-parameter (8) model, and do > the extrapolation.) So pick a model of intermediate complexity, run > it, see how long it takes, and multiply that by 33 million ... (if > each model takes about one second to fit, the analysis will take > about a year to run). > > You might want to look into penalized regression approaches > (e.g. see the glmnet package), which are a much more efficient > approach to this type of problem. > > ______________________________________________ > 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. -- Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 ______________________________________________ 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.
