I am modeling a mediated zero-inflated negative binomial (ZINB) model. i am following the steps of O'Rourke & Vazquez (2019) --> https://www.sciencedirect.com/science/article/abs/pii/S0306460319301078
A few days ago i was running a different ZINB model which ran perfectly fine. However, today i wrote a different model, same variables, but somehow it doesn't run anymore and gives a strange error. When i try my previous model i suddenly get the same error, namely:
Error in zeroinfl(Y1 ~ X1 + M1 | X1 + : object 'model_count' not found
The rest of my code:
#loading required packages
library(psych)
library(foreign)
library(ggplot2)
library(MASS)
library(pscl)
library(nonnest2)
library(lmtest)
library(boot)
#Import data
mydata
#Fit a ZINB model
ex1zinb <- zeroinfl(X1 ~ Y1 + M1 | Y1 + M1, data = mydata, dist="negbin", EM= TRUE)
I already checked the assumption for the statistical analyses etc., and it is especially strange that a similar model did run a few days ago and not anymore. I did try to install several packages today but i ran into a non-zero exit status. Following some comments on stackoverflow i installed a package by adding dependencies = TRUE, but it ran stuck. Afterwards the problems started. Maybe there is something wrong with my packages?
When loading the libraries i get the following messages:
> library(psych)
> library(foreign)
> library(ggplot2)
Need help? Try Stackoverflow: https://stackoverflow.com/tags/ggplot2
Attaching package: ‘ggplot2’
The following objects are masked from ‘package:psych’:
%+%, alpha
> library(MASS)
> library(pscl)
Classes and Methods for R developed in the
Political Science Computational Laboratory
Department of Political Science
Stanford University
Simon Jackman
hurdle and zeroinfl functions by Achim Zeileis
> library(nonnest2)
This is nonnest2 0.5-3.
nonnest2 has not been tested with all combinations of model classes.
> library(lmtest)
Loading required package: zoo
Attaching package: ‘zoo’
The following objects are masked from ‘package:base’:
as.Date, as.Date.numeric
> library(boot)
Attaching package: ‘boot’
The following object is masked from ‘package:psych’:
logit
Anyone some suggestions/insights? Thanks in advance!
Edit: i do get a normal output when running a non-zero inflated negative binomial model. The following code runs smooth:
summary(ex1nb <- glm.nb(Y1~ X1 + M1, data = mydata))
So i think my data is fine?
Details. If the amount of observed zeros is larger than the amount of predicted zeros, the model is underfitting zeros, which indicates a zero-inflation in the data. In such cases, it is recommended to use negative binomial or zero-inflated models.
There is no need to use a zero-inflated Poisson model. You may use the negative binomial regression model since it allows for overdispersion. Now the only question remains whether to use a zero-inflated negative binomial model, which is a special case of the negative binomial model.
I got that error too. I used R 4.0 then tried R 3.6. No luck.
I was able to get the error to go away when I removed the EM = TRUE parameter.
I'm not sure if this helps.
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