Hi, I have 12 independent variables and one dependent variable. Now I want to select the best adj. R squared model by using the regsubsets command, so I code:
plot(regsubsets(Gesamt ~ CommunistSocialist + CountrySize + GNI + Lifeexp
+ Schoolyears + ExpMilitary + Mortality + + PopPoverty + PopTotal + ExpEdu + ExpHealth, data=olympiadaten, nbest=1, nvmax=12), scale='adjr2') Then I get the picture I attached. The problem is, that the best model has an adjusted R squard of 0.49. But if I regress e.g. my y on only the variable PopTotal, then I already get an adjusted R squared of 0.779! So this simple model is way better but it is not recognized by the regsubsets command. I don't know why R does this and how can I change this? And a general question: If I take the best model by AIC, does this model also has the highest (best) adj. R squared? Should I select my models by information criterions or by R squared? And what is exactly the difference, I mean, both take into account the fitting and the nunber of variables right? Thanks a lot! Thanks a lot for your help! -------------- n?chster Teil -------------- Ein Dateianhang mit Bin?rdaten wurde abgetrennt... Dateiname : subsets.png Dateityp : image/png Dateigr??e : 8196 bytes Beschreibung: nicht verf?gbar URL : <https://stat.ethz.ch/pipermail/r-help/attachments/20120925/95425045/attachment.png>