@article{ref1,
title="Statistical methods for developing and distinguishing multinomial response models in the traumatological analysis of simulated automobile impacts",
journal="Proceedings of the International Research Council on the Biomechanics of Injury conference",
year="1988",
author="Haerdle, W. and Kallieris, Dimitrios and Mattern, Rainer",
volume="16",
number="",
pages="47-62",
abstract="This report describes the statistical analysis of injury data involving two sets of data taken from simulated car-to-car side impact studies. Predictors include exogenous biomechanical factors as well as anthropometric variables, such as age. The response is measured on a scale of injury score and is therefore multinomial. It is the aim of a statistical analysis of such data to devise a multinomial response model that explains possible patterns of injury as a function of a suitable set of predictor variables. Several approaches for modelling such a multinomial response relationship have been proposed in the literature, among them the logistic and the weibull regression models. Two major questions in applying such models are as follows: what model is appropriate and how should different models be compared. Another problem is how the quality of a given model should be presented for varying sets of predictors. In this paper we discuss the first question by constructing a goodness-of-fit test based on bootstrapping flexible, non-parametric alternatives to a given parametric candidate model. Secondly, we present several graphical techniques that allow relatively simple comparisons of different models.<p />",
language="en",
issn="2235-3151",
doi="",
url="http://dx.doi.org/"
}