Perhaps a crude but reliable way is to check the number of residuals, e.g., length(my.model$resid).
Brian Brian S. Cade, PhD U. S. Geological Survey Fort Collins Science Center 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: ca...@usgs.gov <brian_c...@usgs.gov> tel: 970 226-9326 On Mon, Mar 18, 2013 at 8:39 AM, Marc Schwartz <marc_schwa...@me.com> wrote: > > On Mar 18, 2013, at 7:36 AM, Federico Calboli <f.calb...@imperial.ac.uk> > wrote: > > > Dear All, > > > > is there a simple way that covers all regression models to extract the > number of samples from a data frame/matrix actually used in a regression > model? > > > > For instance I might have a data of 100 rows and 4 colums (1 response + > 3 explanatory variables). If 3 samples have one or more NAs in the > explanatory variable columns these samples will be dropped in any model: > > > > my.model = lm(y ~ x + w + z, my.data) > > my.model = glm(y ~ x + w + z, my.data, family = binomial) > > my.model = polr(y ~ x + w + z, my.data) > > > > > > I don't seem to be able to find one single method that works in the > exact same way -- irrespective of the model type -- to interrogate my.model > to see how many samples of my.data were actually used. Is there such > function or do I need to hack something together? > > > > Best wishes > > > > Federico > > > I don't know that this would be universal to all possible R model > implementations, but should work for those that at least abide by "certain > standards"[1] relative to the internal use of ?model.frame. > > In the case where model functions use 'model = TRUE' as the default in > their call (eg. lm(), glm() and MASS::polr()), the returned model object > will have a component called 'model', such that: > > nrow(my.model$model) > > returns the number of rows in the internally created data frame. > > Note that 'model = TRUE' is not the default for many functions, for > example Terry's coxph() in survival or Frank's lrm() in rms. > > Note also that the value of 'na.action' in the modeling function call may > have a potential effect on whether the number of rows in the retained > 'model' data frame is really the correct value. > > You can also use model.frame(), independently matching arguments passed to > the model function, to replicate what takes place internally in many > modeling functions. The result of model.frame() will be a data frame, > again, subject to similar limitations as above. > > Regards, > > Marc Schwartz > > [1]: http://developer.r-project.org/model-fitting-functions.txt > > ______________________________________________ > 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. > [[alternative HTML version deleted]]
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