Zero inflated negative binomial regression interpreting main and interaction effects

#1
I am running a zero inflated negative binomial model (zinb) and want to interpret the main and interaction effects.

I have the following:

People decide whether to purchase a good during a given week and I have their final purchase quantity (Min qty = 0 units and Max qty = 10 units observed from the data). Assume I am looking at the results for a particular week. I have multiple demographics variable but two discrete variables are imp namely:

education (=1 if buyer has college degree, 0 otherwise) and
gender (1 = female, 0 = male).

Due to the presence of a large number of 0's and overdispersion, I use a zinb model.
The code I use on Stata:
zinb purchase_qty i.gender##i.educ, inflate (c.age)

The regression results are (not presenting results for the inflation part here):

HTML:
purchase_qty                            Coef.    P>|z|
     1.gender                           -0.26    0.028
     1.education                        -0.07    0
     gender##education 1 1               0.12    0.027
     _cons                              -0.5     0.56
What I want to calculate from the above table is the average qty purchased by the four groups:
Group1 - gender=0 & educ=0
Group 2 - gender=1 & educ=0
Group3 - gender=0 & educ=1
Group 4 - gender=1 & educ=1.

Could someone please explain how to do this from the above output(taking into account that main effect and interaction effect are significant)?

Thanks.
 

hlsmith

Omega Contributor
#2
Re: Zero inflated negative binomial regression interpreting main and interaction effe

Are you familiar with logistic regression?
 

rogojel

TS Contributor
#5
Re: Zero inflated negative binomial regression interpreting main and interaction effe

hi,
the simplest way would be to use the predict functionality with the model. I do not know Stata, but I am sure it must offer predictions based on the model.

regards