Semiparametric Negative Binomial Regression Models |
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Authors: | Chin-Shang Li |
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Institution: | 1. Department of Public Health Sciences, Division of Biostatistics , University of California , Davis, California, USA cssli@ucdavis.edu |
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Abstract: | Negative-binomial (NB) regression models have been widely used for analysis of count data displaying substantial overdispersion (extra-Poisson variation). However, no formal lack-of-fit tests for a postulated parametric model for a covariate effect have been proposed. Therefore, a flexible parametric procedure is used to model the covariate effect as a linear combination of fixed-knot cubic basis splines or B-splines. Within the proposed modeling framework, a log-likelihood ratio test is constructed to evaluate the adequacy of a postulated parametric form of the covariate effect. Simulation experiments are conducted to study the power performance of the proposed test. |
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Keywords: | B-spline Lack-of-fit test Log-likelihood ratio test Negative binomial Overdispersion Profile likelihood |
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