On testing the hidden heterogeneity in negative binomial regression models

Jeonghwan Kim and Woojoo Lee ()
Additional contact information
Jeonghwan Kim: Inha University
Woojoo Lee: Inha University

Metrika: International Journal for Theoretical and Applied Statistics, 2019, vol. 82, issue 4, No 4, 457-470

Abstract: Abstract Negative binomial regression models have been widely used for analyzing overdispersed count data. However, when an important covariate is not included or individuals show some heterogeneity, negative binomial regression models may lead to erroneous standard errors or confidence intervals for the regression parameters. To test the existence of the hidden heterogeneity in negative binomial regression models, score statistics are developed under additive and multiplicative random effect models. We provide the explicit form of the score test statistics and their asymptotic distribution, and investigate the relationship between the score test statistics from the two random effect models. Our numerical study shows that the proposed score statistic has superior performance than existing methods in terms of controlling for the type I error and power.

Keywords: Negative binomial regression; Hidden heterogeneity; Random effect model; Score test (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00184-018-0684-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:metrik:v:82:y:2019:i:4:d:10.1007_s00184-018-0684-x

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s00184-018-0684-x

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().