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

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  • S. le Cessie
  • J. C. van Houwelingen

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.

Suggested Citation

  • S. le Cessie & J. C. van Houwelingen, 1993. "Building logistic models by means of a non parametric goodness of fit test: a case study," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 47(2), pages 97-109, June.
  • Handle: RePEc:bla:stanee:v:47:y:1993:i:2:p:97-109
    DOI: 10.1111/j.1467-9574.1993.tb01410.x
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