Re: [R] Obtaining a value of pie in a zero inflated model (fm-zinb2)
A little more. As Christopher Ryan points out, as long as the zero-inflation model is non-trivial (i.e. more complex than a single intercept for the whole population), there's a pi(i) for every observation i (you could certainly average the pi(i) values if you wanted, or compute pi for an averaged set of covariates). library(pscl) fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist = "poisson") pi_i <- predict(fm_zinb2, type = "zero") head(pi_i) ## 1 2 3 4 5 6 ## 0.13392803 0.21936320 0.21973454 0.24697313 0.01890023 0.34281196 To get the conditional probability that a zero observation is a structural or a sampling zero, compute the probability of a sampling zero (exp(-mu[i]) for a Poisson model) and use Bayes' rule, assuming equal prior probs ## probability of _sampling_ zero psampz <- exp(-predict(fm_zinb2, type = "count")) head(psampz) ## 1 2 3 4 5 6 ## 0.09507376 0.18361241 0.18688646 0.14774602 0.08992667 0.27235498 pz <- 1 - (1-pi_i)*(1-psampz) ## prob of zero of either type ## 1 2 3 4 5 6 ## 0.2162687 0.3626978 0.366 0.3582299 0.1071273 0.5218004 psampz/pz head(psampz)/head(pz) ## 1 2 3 4 5 6 ## 0.4396093 0.5062408 0.5112395 0.4124336 0.8394378 0.5219524 3. I'm not aware of a closed-form solution for zero-inflation models as long as the count and/or structural-zero components depend on covariates? In any case, looking inside zeroinfl() you can see that it calls optim() [using BFGS by default, see ?pscl::zeroinfl.control] cheers Ben Bolker On 2024-01-04 9:38 a.m., Christopher W. Ryan via R-help wrote: 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@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. __ R-help@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. __ R-help@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.
Re: [R] Obtaining a value of pie in a zero inflated model (fm-zinb2)
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@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. > __ R-help@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.
[R] 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 __ R-help@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.
