R help - Jan 2024 - Obtaining a value of pie in a zero inflated model (fm-zinb2)

I am running a zero inflated regression using the zeroinfl function similar to
the model below:
  
 fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist =
"poisson")
summary(fm_zinb2)

I have three questions:

1) How can I obtain a value for the parameter pie, which is the fraction of the
population that is in the zero inflated model vs the fraction in the count
model?

2) For any particular subject, how can I determine if the subject is in the
portion of the population that contributes a zero count because the subject is
in the group of subjects who have structural zero responses vs. the subject
being in the portion of the population who can contribute a zero or a non-zero
response?

3) zero inflated models can be solved using closed form solutions, or using
iterative methods. Which method is used by fm_zinb2?

Thank you,
John

John David Sorkin M.D., Ph.D.
Professor of Medicine, University of Maryland School of Medicine;

Associate Director for Biostatistics and Informatics, Baltimore VA Medical
Center Geriatrics Research, Education, and Clinical Center;?

PI?Biostatistics and Informatics Core, University of Maryland School of Medicine
Claude D. Pepper Older Americans Independence Center;

Senior Statistician University of Maryland Center for Vascular Research;

Division of Gerontology and Paliative Care,
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
Cell phone 443-418-5382

Are you referring to the zeroinfl() function in the countreg package? If
so, I think

predict(fm_zinb2, type = "zero", newdata = some.new.data)

will give you pi for each combination of covariate values that you
provide in some.new.data

where pi is the probability to observe a zero from the point mass component.

As to your second question, I'm not sure that's possible, for any
*particular, individual* subject. Others will undoubtedly know better
than I.

--Chris Ryan

Sorkin, John wrote:
> I am running a zero inflated regression using the zeroinfl function similar
to the model below:
>   
>  fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist =
"poisson")
> summary(fm_zinb2)
> 
> I have three questions:
> 
> 1) How can I obtain a value for the parameter pie, which is the fraction of
the population that is in the zero inflated model vs the fraction in the count
model?
> 
> 2) For any particular subject, how can I determine if the subject is in the
portion of the population that contributes a zero count because the subject is
in the group of subjects who have structural zero responses vs. the subject
being in the portion of the population who can contribute a zero or a non-zero
response?
> 
> 3) zero inflated models can be solved using closed form solutions, or using
iterative methods. Which method is used by fm_zinb2?
> 
> Thank you,
> John
> 
> John David Sorkin M.D., Ph.D.
> Professor of Medicine, University of Maryland School of Medicine;
> 
> Associate Director for Biostatistics and Informatics, Baltimore VA Medical
Center Geriatrics Research, Education, and Clinical Center;?
> 
> PI?Biostatistics and Informatics Core, University of Maryland School of
Medicine Claude D. Pepper Older Americans Independence Center;
> 
> Senior Statistician University of Maryland Center for Vascular Research;
> 
> Division of Gerontology and Paliative Care,
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> Cell phone 443-418-5382
> 
> 
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>