Sorry that this error has been discussed before, each answer on stackoverflow seems specific to the data
I'm attempting to run the following negative binomial model in lme4:
Model5.binomial<-glmer.nb(countvariable ~ waves + var1 + dummycodedvar2 + dummycodedvar3 + (1|record_id), data=datadfomit)
However, I receive the following error when attempting to run the model:
Error in f_refitNB(lastfit, theta = exp(t), control = control) :pwrssUpdate did not converge in (maxit) iterations
I first ran the model with only 3 predictor variables (waves, var1, dummycodedvar2) and got the same error. But centering the predictors fixed this problem and the model ran fine.
Now with 4 variables (all centered) I expected the model to run smoothly, but receive the error again.
Since every answer on this site seems to point towards a problem in the data, data that replicates the problem can be found here:
https://file.io/3vtX9RwMJ6LF
Your response variable has a lot of zeros:
I would suggest fitting a model that takes account of this, such as a zero-inflated model. The
GLMMadaptive
package can fit zero-inflated negative binomial mixed effects models: