Testing the Lack-of-Fit of Zero-Inflated Poisson Regression Models

作者：Li Chin Shang^*

来源：Communications in Statistics - Simulation and Computation, 2011, 40(4): 497-510.

DOI：10.1080/03610918.2010.546541

• B-splines
• Expectation-maximization (EM) algorithm
• Lack-of-fit test
• Log-likelihood ratio test

A zero-inflated Poisson regression model has been widely used for the effect of a covariate in count data containing many zeros with a linear predictor. To assess the adequacy of the linear relationship, we approximate the covariate effect with cubic B-splines. The semiparametric model parameters are estimated by maximizing the likelihood function through an expectation-maximization algorithm. A log-likelihood ratio test is then used to evaluate the adequacy of the linear relation. A simulation study is conducted to study the power performance of the test. A real example is provided to demonstrate the practical use of the methodology.

• 出版日期2011