title: A Spline-Based Lack-Of-Fit Test for Independent Variable Effect in Poisson Regression.
abstract: In regression analysis of count data, independent variables are often modeled by their linear effects under the assumption of log-linearity. In reality, the validity of such an assumption is rarely tested, and its use is at times unjustifiable. A lack-of-fit test is proposed for the adequacy of a postulated functional form of an independent variable within the framework of semiparametric Poisson regression models based on penalized splines. It offers added flexibility in accommodating the potentially non-loglinear effect of the independent variable. A likelihood ratio test is constructed for the adequacy of the postulated parametric form, for example log-linearity, of the independent variable effect. Simulations indicate that the proposed model performs well, and misspecified parametric model has much reduced power. An example is given.
authors.affiliation: Department of Biostatistics at St. Jude Children's Research Hospital, Memphis, Tennessee.
authors.forename: Chin-Shang
authors.initials: CS
authors.lastname: Li
authors.forename: Wanzhu
authors.initials: W
authors.lastname: Tu