Now, what I would like to know is:Ī) How do I interpret the second block of the model in relation to the first block? As you can see in the results, some variables are significant in both the first and the second block. The second block (the zero component), on the other hand, predicts whether or not the outcome is a certain zero. Number of iterations in BFGS optimization: 42Īs far as I understand, the first block (the count component) is a summary of the full model and can be interpreted as a standard negative binomial model. Zeroinfl(formula = CRIME ~ VAR1 + VAR2 + VAR3 + VAR4 + VAR5 Information about your sample, including any missing values (e.g., sample size). An introduction to the analysis you carried out (e.g., state that you ran a binomial logistic regression). When you report the output of your binomial logistic regression, it is good practice to include: A. Below is my model and the results: #estimate zero-inflated NB model Reporting the output of a binomial logistic regression. The model seems to work OK, but I'm uncertain on how to interpret the results. I am trying to estimate a zero-inflated negative binomial model with 11 predictor variables and the number of reported crimes as a response variable.
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