If you are trying to destroy all aspects of statistical inference this is a good way to go. This is also a good way to ignore the subject matter in driving model selection. Frank
Jhope wrote > > Hi R-listers, > > I have developed 47 GLM models with different combinations of interactions > from 1 variable to 5 variables. I have manually made each model separately > and put them into individual tables (organized by the number of variables) > showing the AIC score. I want to compare all of these models. > > 1) What is the best way to compare various models with unique combinations > and different number of variables? > 2) I am trying to develop the most simplest model ideally. Even though > adding another variable would lower the AIC, how do I interpret it is > worth it to include another variable in the model? How do I know when to > stop? > > Definitions of Variables: > HTL - distance to high tide line (continuous) > Veg - distance to vegetation > Aeventexhumed - Event of exhumation > Sector - number measurements along the beach > Rayos - major sections of beach (grouped sectors) > TotalEggs - nest egg density > > Example of how all models were created: > Model2.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ Aeventexhumed, > data=data.to.analyze, family=binomial) > Model7.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ HTL:Veg, family = > binomial, data.to.analyze) > Model21.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ HTL:Veg:TotalEggs, > data.to.analyze, family = binomial) > Model37.glm <- glm(cbind(Shells, TotalEggs-Shells) ~ > HTL:Veg:TotalEggs:Aeventexhumed, data.to.analyze, family=binomial) > > Please advise, thanks! > J > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/How-do-I-compare-47-GLM-models-with-1-to-5-interactions-and-unique-combinations-tp4326407p4327219.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.