Hello,
Firstly, apologies because this is a resubmission of question that I sent previously that I think was poorly worded and did not get a response. Apologies if resubmission of a reworded question is not considered appropriate.
My question is how to get the predicted counts based on BOTH parts of the two part Hurdle model, as outlined below. I think they need to be calculated by hand but I am not sure how to do this. Does anyone know of a worked example or a book chapter.
I have used 'Health Econometrics Using Stata by Partha Deb Edward C . Norton Willard G. Manning' & 'Generalized Linear Models and Extensions by James W. Hardin, Joseph M. Hilbe' - and while being excellent books generally, do not provide guidance on getting the predicted counts for the entire dataset based on both parts of the model.
I am using data from http://www.stata-press.com/data/heus/heus_mepssample
I am using these sample data from Stata to understand the model before applying the methodology to my data.
I am trying to implement a hurdle model, with the first part being a logit model and the second part being a negative binomial model.
I have implemented the following for the first part:
*create dependent variable for the logit model:
gen pzero = use_off
replace pzero = 1 if use_off >0
logit pzero age i.female
estimates store h1
predict xb1
for the second part if have implemented the following:
tnbreg use_off age i.female if use_off >0
predict xb2 if use_off >0
estimates store h2
suest h1 h2
Firstly, apologies because this is a resubmission of question that I sent previously that I think was poorly worded and did not get a response. Apologies if resubmission of a reworded question is not considered appropriate.
My question is how to get the predicted counts based on BOTH parts of the two part Hurdle model, as outlined below. I think they need to be calculated by hand but I am not sure how to do this. Does anyone know of a worked example or a book chapter.
I have used 'Health Econometrics Using Stata by Partha Deb Edward C . Norton Willard G. Manning' & 'Generalized Linear Models and Extensions by James W. Hardin, Joseph M. Hilbe' - and while being excellent books generally, do not provide guidance on getting the predicted counts for the entire dataset based on both parts of the model.
I am using data from http://www.stata-press.com/data/heus/heus_mepssample
I am using these sample data from Stata to understand the model before applying the methodology to my data.
I am trying to implement a hurdle model, with the first part being a logit model and the second part being a negative binomial model.
I have implemented the following for the first part:
*create dependent variable for the logit model:
gen pzero = use_off
replace pzero = 1 if use_off >0
logit pzero age i.female
estimates store h1
predict xb1
for the second part if have implemented the following:
tnbreg use_off age i.female if use_off >0
predict xb2 if use_off >0
estimates store h2
suest h1 h2
