Hello, I am trying to estimate the number of correct predictions in a linear model using robust and a linear model with wls. My instructor showed doing this regress diab owgt obese exer cig alc inc coll marr male age, robust
predict probl, xb
generate cdiab=(probl >=0.5 & diab==1)
generate cnodiab=(probl <0.5 & diab==0)
generate correct =(cdiab==1 | cnodiab==1)
sum diab cdiab cnodiab correct
but is this specific for either model? And it only prints out this:
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
diab | 5,051 .1282914 .3344471 0 1
cdiab | 5,051 0 0 0 0
cnodiab | 5,051 .8717086 .3344471 0 1
correct | 5,051 .8717086 .3344471 0 1
It does not include a table that shows the predictions as the instructor said it would. Can anyone tell me if the information I need is hidden in here or if I did something wrong?
Thank you
predict probl, xb
generate cdiab=(probl >=0.5 & diab==1)
generate cnodiab=(probl <0.5 & diab==0)
generate correct =(cdiab==1 | cnodiab==1)
sum diab cdiab cnodiab correct
but is this specific for either model? And it only prints out this:
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
diab | 5,051 .1282914 .3344471 0 1
cdiab | 5,051 0 0 0 0
cnodiab | 5,051 .8717086 .3344471 0 1
correct | 5,051 .8717086 .3344471 0 1
It does not include a table that shows the predictions as the instructor said it would. Can anyone tell me if the information I need is hidden in here or if I did something wrong?
Thank you
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