Bootstrap tests for overdispersion in a zero-inflated Poisson regression model.
Ridout, Hinde, and Demétrio (2001, Biometrics 57, 219-223) derived a score test for testing a zero-inflated Poisson (ZIP) regression model against zero-inflated negative binomial (ZINB) alternatives. They mentioned that the score test using the normal approximation might underestimate the nominal significance level possibly for small sample cases. To remedy this problem, a parametric bootstrap method is proposed. It is shown that the bootstrap method keeps the significance level close to the nominal one and has greater power uniformly than the existing normal approximation for testing the hypothesis.
Jung
Byoung Cheol
BC
Department of Statistics, Sungshin University, Seoul 136-742, Korea.
Jhun
Myoungshic
M
Lee
Jae Won
JW
D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D015233:Models, Statistical; D009010:Monte Carlo Method; D018517:Plant Roots / Q000254:growth & development; D016012:Poisson Distribution; D012044:Regression Analysis