Abstract
When a count data set has excessive zero counts, nonzero counts are overdispersed, and the effect of a continuous covariate might be nonlinear, for analysis a semiparametric zero-inflated negative binomial (ZINB) regression model is proposed. The unspecified smooth functional form for the continuous covariate effect is approximated by a cubic spline. The semiparametric ZINB regression model is fitted by maximizing the likelihood function. The likelihood ratio procedure is used to evaluate the adequacy of a postulated parametric functional form for the continuous covariate effect. An extensive simulation study is conducted to assess the finite-sample performance of the proposed test. The practicality of the proposed methodology is demonstrated with data of a motorcycle survey of traffic regulations conducted in 2007 in Taiwan by the Ministry of Transportation and Communication.
| Original language | English (US) |
|---|---|
| Journal | Journal of Statistical Computation and Simulation |
| DOIs | |
| State | Published - Jan 1 2019 |
| Externally published | Yes |
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Keywords
- B-splines
- count data
- likelihood ratio
- overdispersion
- zero-inflated negative binomial
- zero-inflated Poisson
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Statistics, Probability and Uncertainty
- Applied Mathematics
Cite this
A test for lack-of-fit of zero-inflated negative binomial models. / Li, Chin-Shang; Lee, Shen Ming; Yeh, Ming Shan.
In: Journal of Statistical Computation and Simulation, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A test for lack-of-fit of zero-inflated negative binomial models
AU - Li, Chin-Shang
AU - Lee, Shen Ming
AU - Yeh, Ming Shan
PY - 2019/1/1
Y1 - 2019/1/1
N2 - When a count data set has excessive zero counts, nonzero counts are overdispersed, and the effect of a continuous covariate might be nonlinear, for analysis a semiparametric zero-inflated negative binomial (ZINB) regression model is proposed. The unspecified smooth functional form for the continuous covariate effect is approximated by a cubic spline. The semiparametric ZINB regression model is fitted by maximizing the likelihood function. The likelihood ratio procedure is used to evaluate the adequacy of a postulated parametric functional form for the continuous covariate effect. An extensive simulation study is conducted to assess the finite-sample performance of the proposed test. The practicality of the proposed methodology is demonstrated with data of a motorcycle survey of traffic regulations conducted in 2007 in Taiwan by the Ministry of Transportation and Communication.
AB - When a count data set has excessive zero counts, nonzero counts are overdispersed, and the effect of a continuous covariate might be nonlinear, for analysis a semiparametric zero-inflated negative binomial (ZINB) regression model is proposed. The unspecified smooth functional form for the continuous covariate effect is approximated by a cubic spline. The semiparametric ZINB regression model is fitted by maximizing the likelihood function. The likelihood ratio procedure is used to evaluate the adequacy of a postulated parametric functional form for the continuous covariate effect. An extensive simulation study is conducted to assess the finite-sample performance of the proposed test. The practicality of the proposed methodology is demonstrated with data of a motorcycle survey of traffic regulations conducted in 2007 in Taiwan by the Ministry of Transportation and Communication.
KW - B-splines
KW - count data
KW - likelihood ratio
KW - overdispersion
KW - zero-inflated negative binomial
KW - zero-inflated Poisson
UR - http://www.scopus.com/inward/record.url?scp=85061577896&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061577896&partnerID=8YFLogxK
U2 - 10.1080/00949655.2019.1577856
DO - 10.1080/00949655.2019.1577856
M3 - Article
JO - Journal of Statistical Computation and Simulation
JF - Journal of Statistical Computation and Simulation
SN - 0094-9655
ER -