EconPapers    
Economics at your fingertips  
 

Bivariate Negative Binomial and Multinomial Models

M. Ataharul Islam () and Rafiqul I. Chowdhury
Additional contact information
M. Ataharul Islam: University of Dhaka, Institute of Statistical Research and Training (ISRT)
Rafiqul I. Chowdhury: University of Dhaka, Institute of Statistical Research and Training (ISRT)

Chapter Chapter 9 in Analysis of Repeated Measures Data, 2017, pp 125-138 from Springer

Abstract: Abstract In this chapter, the generalized linear models for bivariate negative binomial or more specifically negative multinomial and bivariate multinomial models are presented. It is often necessary to use multinomial and negative binomial distributions for representing a set of counts as possible outcomes. In other words, these models can be used as alternative to Poisson models in case of under- or overdispersion. An alternative procedure for addressing the overdispersion problem is illustrated in this chapter based on the connection between Poisson and multinomial for both marginal and conditional models which are used to develop the bivariate multinomial model. Tests for goodness of fit, overdispersion, and comparison of models are also shown for bivariate count data using both negative multinomial and bivariate multinomial models. The estimation and test procedures are illustrated with examples. For comparison of models, a generalized Voung test is also illustrated.

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-10-3794-8_9

Ordering information: This item can be ordered from
http://www.springer.com/9789811037948

DOI: 10.1007/978-981-10-3794-8_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-07-12
Handle: RePEc:spr:sprchp:978-981-10-3794-8_9