I want to select models using regsubsets. I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code is:

attach(olympiadaten)

library(leaps)
a<-regsubsets(Gesamt ~ CommunistSocialist + CountrySize + GNI + Lifeexp + Schoolyears + ExpMilitary + Mortality +
PopPoverty + PopTotal + ExpEdu + ExpHealth, data=olympiadaten, nbest=2)
summary(a)
plot(a,scale="adjr2")


summary(lm(Gesamt~ExpHealth))

screenshot of the plot: http://tinypic.com/r/2pq8agy/6

The graphic says, it should have an adjusted R squared of about 0.14, but when I look at the output, I get a value of 0.06435

output of : summary(lm(Gesamt~ExpHealth))

I don't know what I might have done wrong, any help would be appreciated, thanks. (I could not attach both files correctly, maybe a moderator can attach them correctly, thanks).

And last but not least, some more questions: What is the difference between selecting models by AIC and by the adj. R squared? Both measure the fit and recognize the number of variables, so isn't the best model choosen by AIC also the model with the highest adj. r squared?

When I have 12 variables, this means, there are 2^12 possibilites of models, right? So does the regsubsets command calculate each model and shows the two best (nbest=2) of each size? If so do I really get the 'best' model? And when I do AIC using backwards selection (starting with the model which contains all variables), does this also end up with the same model that regsubsets says is the best?

I want to select models using regsubsets(). I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code is:

attach(olympiadaten)

library(leaps)
a<-regsubsets(Gesamt ~ CommunistSocialist + CountrySize + GNI + Lifeexp + 
              Schoolyears + ExpMilitary + Mortality +
PopPoverty + PopTotal + ExpEdu + ExpHealth, data=olympiadaten, nbest=2)
summary(a)
plot(a,scale="adjr2")


summary(lm(Gesamt~ExpHealth))

screenshot of the plot:

The graphic says, it should have an adjusted R squared of about 0.14, but when I look at the output, I get a value of 0.06435.

Here is the output of summary(lm(Gesamt~ExpHealth)):

I don't know what I might have done wrong, any help would be appreciated.

And last but not least, some more questions:

• What is the difference between selecting models by AIC and by the adj. R squared?
• Both measure the fit and recognize the number of variables, so isn't the best model chosen by AIC also the model with the highest adj. r squared?
• When I have 12 variables, this means, there are $2^12$ possibilities of models, right?
• So does the regsubsets() command calculate each model and show the two best (nbest=2) of each size?
• If so, do I really get the 'best' model?
• And when I do AIC using backwards selection (starting with the model which contains all variables), does this also end up with the same model that regsubsets() says is the best?

I want to select models with regsubsets. I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code:

I don't know which mistake I did, any help would be nice, thanks. (I could not attach both files correctly, maybe a mode can attach them correctly, thanks).

And last but not least, some more questions: What is the difference between selecting models by AIC and by the adj. R squared? Both measure the fit and recognize the number of variables, so is the best model choosen by AIC also the model with the highest adj. r squared?

When I have 12 variables, this means, there are 2^12 possibilites of models, right? So does the regsubsets command calculate each model and shows the two best (nbest=2) of each size? So do I really get the 'best' model? And when I do stepwise AIC backwards selection (starting with the model which contains all variables), does this also ends with the same model as regsubsets says it is the best?

I want to select models using regsubsets. I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code is:

I don't know what I might have done wrong, any help would be appreciated, thanks. (I could not attach both files correctly, maybe a moderator can attach them correctly, thanks).

And last but not least, some more questions: What is the difference between selecting models by AIC and by the adj. R squared? Both measure the fit and recognize the number of variables, so isn't the best model choosen by AIC also the model with the highest adj. r squared?

When I have 12 variables, this means, there are 2^12 possibilites of models, right? So does the regsubsets command calculate each model and shows the two best (nbest=2) of each size? If so do I really get the 'best' model? And when I do AIC using backwards selection (starting with the model which contains all variables), does this also end up with the same model that regsubsets says is the best?

I want to make model selection with regsubsets. I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code:

I want to select models with regsubsets. I have a dataframe called olympiadaten (data uploaded: http://www.sendspace.com/file/8e27d0). I first attach this dataframe and then start to analyze, my code: