Building logistic models by means of a non parametric goodness of fit test: a case study

S. le Cessie and J. C. van Houwelingen

Statistica Neerlandica, 1993, vol. 47, issue 2, 97-109

Abstract: A sequence of logistic models is fitted to data from a Dutch follow‐up study on preterm infants (POPS). To examine the adequacy of the model, a recently developed non parametric method to check goodness of fit is applied (le Cessie and Van Houwelingen (1991)). This method uses a test statistic based upon kernel regression methods. In this paper the problem of choosing a “best” bandwidth, corresponding to the greatest power of the test statistic, is avoided by computing the test statistic for a range of different bandwidths. Testing is then based upon the asymptotic distribution of the maximum of the test statistics. The testing method is used as a goodness of fit criterion, and the contribution of each individual observation to the test statistic is used as a diagnostic tool to localize deviations of the model, and to determine directions in which the model can be improved.

Date: 1993
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