Parameter estimation on zero-inflated negative binomial regression with right truncated data

A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression mod...

Full description

Bibliographic Details
Main Authors: Seyed Ehsan Saffari, Robiah Adnan
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2012
Online Access:http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf
_version_ 1848810877323575296
author Seyed Ehsan Saffari,
Robiah Adnan,
author_facet Seyed Ehsan Saffari,
Robiah Adnan,
author_sort Seyed Ehsan Saffari,
building UKM Institutional Repository
collection Online Access
description A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodness-of-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated.
first_indexed 2025-11-14T23:37:29Z
format Article
id oai:generic.eprints.org:5586
institution Universiti Kebangasaan Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T23:37:29Z
publishDate 2012
publisher Universiti Kebangsaan Malaysia
recordtype eprints
repository_type Digital Repository
spelling oai:generic.eprints.org:55862016-12-14T06:38:53Z http://journalarticle.ukm.my/5586/ Parameter estimation on zero-inflated negative binomial regression with right truncated data Seyed Ehsan Saffari, Robiah Adnan, A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodness-of-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated. Universiti Kebangsaan Malaysia 2012-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf Seyed Ehsan Saffari, and Robiah Adnan, (2012) Parameter estimation on zero-inflated negative binomial regression with right truncated data. Sains Malaysiana, 41 (11). pp. 1483-1487. ISSN 0126-6039 http://www.ukm.my/jsm/
spellingShingle Seyed Ehsan Saffari,
Robiah Adnan,
Parameter estimation on zero-inflated negative binomial regression with right truncated data
title Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_full Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_fullStr Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_full_unstemmed Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_short Parameter estimation on zero-inflated negative binomial regression with right truncated data
title_sort parameter estimation on zero-inflated negative binomial regression with right truncated data
url http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/
http://journalarticle.ukm.my/5586/1/19%2520Seyed%2520Ehsan.pdf