library(Rcmdr)
library(RcmdrPlugin.HH) 

Mireault <- read.table("http://www.unt.edu:8080/rss/class/mike/data/Mireault.dat", na.strings=".", header=T)

attach(Mireault)

Subsets.1 <- regsubsets(DepressT ~AnxT+HostT+ObsessT+ParT+PhobT+PsyT+SensitT+SomT, data=Mireault, nbest=2)
Subsets.1.Summary <- summary_HH(Subsets.1)
Subsets.1.Summary   #subset 11 has largest adjr2, Model 9 is the same as 11, but without the PhobT variable. Model 9 is best in terms of having the lowest BIC and Mallow's Cp 
plot(Subsets.1.Summary, statistic='adjr2')
RegModel.1.11 <- lm.regsubsets(Subsets.1, 11)  ## subset 11 has largest adjr2
summary(RegModel.1.11)