Hello,
I am attempting a two-part model on semi-continuous data (zero inflated).
As I understand, the first part is a binary logistic regression (or probit) model for the dichotomous event of having zero or positive values.
logit[P(Yi = 0)] = xβ ......... Equation (1)
Conditional on a positive / non-zero value, the second part (continuous) can be modelled using either a OLS regression (with or without log-normal transformation of outcome variable) or generalized linear models (GLM).
log(yi|yi > 0) = xβ2 + e where e is normally distributed .... Eq (2)
Combining the above two parts, the overall mean can be written as the PRODUCT of expectations from the first and second parts of the model (refer Eq 1 and 2), as follows:
E(y|x)=Pr(y> 0|x) ×E(y|y> 0, x) .... Eq (3).
I could find a no. of papers which have employed the 'twopm' command of STATA package. However, I am using SPSS. I have conducted the two parts (binary and continuous) using the same set of predictors.
Please suggest how to multiply the results from both the parts using SPSS.
Thank you.
You might want to look at.the attached screenshot search. A package in R is available. If you aren't familiar with R I suggest you download jarad Lander R for everyone available from the z-library. All of this is free. Best wishes, David Booth
David Eugene Booth Thank you Prof. Booth for your kind response. I have looked into Devin Incerti's and Belotti's works which appear in the search results. Unfortunately, I am not familiar with R. I shall try, as suggested. Thanks again.
David is right; unfortunately, SPSS is unable to run two-part mixture modeling. Stata can run hurdle models (https://www.stata.com/stata14/hurdle-models/). If your university library has Stata installed, that might be faster than learning R. SAS can also run through PROBMODEL statement; however, R remains the best for statistical computing in a long run.
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