Model fitting of zero-inflated and overdispersed count data

Researchers often encounter data which exhibit an excess number of zeroes than would be expected in a Poisson or negative binominal model. This is referred to as zero-inflation. Additionally, data may display excess variability or overdispersion. Failure to model zero-inflation and overdispersion ma...

Full description

Saved in:
Bibliographic Details
Main Authors: Andan, Jacqueline S., Cortez, Andrea P.
Format: text
Published: Animo Repository 2010
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/11326
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
id oai:animorepository.dlsu.edu.ph:etd_bachelors-11971
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-119712021-08-28T03:42:03Z Model fitting of zero-inflated and overdispersed count data Andan, Jacqueline S. Cortez, Andrea P., Researchers often encounter data which exhibit an excess number of zeroes than would be expected in a Poisson or negative binominal model. This is referred to as zero-inflation. Additionally, data may display excess variability or overdispersion. Failure to model zero-inflation and overdispersion may lead to serious underestimation of standard errors and misleading regression parameter estimates. Poisson, negative binomial, zero-inflated Poison (ZIP) and zero-inflated negative binomial (ZINB) regression models are applied to CBMS Pasay City Poverty Census of 2005. Barangays are ranked according to estimated proportion of households below food poverty line. Overdispersion parameters indicate that the data is overdispersed and hence, a negative binomial model is preferred over Poisson model. However, zero-inflation parameters pose no significant evidence that the data is zero-inflated. Accordingly, goodness of fit statistics for the over-al best fit model show that the negative binomial regression model is the most preferred. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/11326 Bachelor's Theses Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
description Researchers often encounter data which exhibit an excess number of zeroes than would be expected in a Poisson or negative binominal model. This is referred to as zero-inflation. Additionally, data may display excess variability or overdispersion. Failure to model zero-inflation and overdispersion may lead to serious underestimation of standard errors and misleading regression parameter estimates. Poisson, negative binomial, zero-inflated Poison (ZIP) and zero-inflated negative binomial (ZINB) regression models are applied to CBMS Pasay City Poverty Census of 2005. Barangays are ranked according to estimated proportion of households below food poverty line. Overdispersion parameters indicate that the data is overdispersed and hence, a negative binomial model is preferred over Poisson model. However, zero-inflation parameters pose no significant evidence that the data is zero-inflated. Accordingly, goodness of fit statistics for the over-al best fit model show that the negative binomial regression model is the most preferred.
format text
author Andan, Jacqueline S.
Cortez, Andrea P.,
spellingShingle Andan, Jacqueline S.
Cortez, Andrea P.,
Model fitting of zero-inflated and overdispersed count data
author_facet Andan, Jacqueline S.
Cortez, Andrea P.,
author_sort Andan, Jacqueline S.
title Model fitting of zero-inflated and overdispersed count data
title_short Model fitting of zero-inflated and overdispersed count data
title_full Model fitting of zero-inflated and overdispersed count data
title_fullStr Model fitting of zero-inflated and overdispersed count data
title_full_unstemmed Model fitting of zero-inflated and overdispersed count data
title_sort model fitting of zero-inflated and overdispersed count data
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/etd_bachelors/11326
_version_ 1712577455060942848