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

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

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Abstract

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.

Item Type:Article
Keywords:Maximum likelihood; truncated data; zero-inflated negative binomial
Journal:Sains Malaysiana
ID Code:5586
Deposited By: Mr Azam
Deposited On:18 Oct 2012 03:55
Last Modified:14 Dec 2016 06:38

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