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Thread: Zero inflated negative binomial regression interpreting main and interaction effects

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    Zero inflated negative binomial regression interpreting main and interaction effects




    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 Code: 
    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.

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    Re: Zero inflated negative binomial regression interpreting main and interaction effe

    Are you familiar with logistic regression?
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    Re: Zero inflated negative binomial regression interpreting main and interaction effe

    Yes I am. Can you explain what you meant in the last post?

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    Re: Zero inflated negative binomial regression interpreting main and interaction effe

    Check this out, in particular the exp(coefficients), same premise as logistic reg.

    http://stats.idre.ucla.edu/stata/out...al-regression/
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    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

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