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
Related Posts with percent of correct predictions
Regression commands for Panel dataHi everyone, I'm trying to estimate this panel data model with the equation below: Array αi is a c…
xtreg default estimator?Hello, This may be a rookie question, but if I run the xtreg without specifying an fe, re, be, or pa…
marginal effect graphs after using GMM for continuous variablesWith due respect I want to make two ways marginal graph to find marginal effect at different percent…
2 Different Fixed Effects with many dummy variablesHi Everyone, I am trying to estimate the following model: Y_ijt = alpha + Beta1*X1 + Beta2*X2 + Be…
Multicollinearity issue between individual-specific variables in the conditional logit modelsHi! I'm currently analyzing survey data (916 respondents in total) using the -asclogit- or -cmclogi…
Subscribe to:
Post Comments (Atom)
0 Response to percent of correct predictions
Post a Comment