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A semiparametric Wald statistic for testing logistic regression models based on case-control data

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Abstract

We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data. The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator. The statistic has an asymptotic chisquared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997, the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001. The statistic is easy to compute in the sense that it requires none of the following methods: using a bootstrap method to find its critical values, partitioning the sample data or inverting a high-dimensional matrix. We present some results on simulation and on analysis of two real examples. Moreover, we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.

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Authors and Affiliations

  1. Biostatistics Lab, School of Life Sciences, Nanjing University, Nanjing, 210093, China

    ShuWen Wan

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  1. ShuWen Wan
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Correspondence to ShuWen Wan.

Additional information

This work was supported by the 11.5 Natural Scientific Plan (Grant No. 2006BAD09A04) and Nanjing University Start Fund (Grant No. 020822410110)

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Wan, S. A semiparametric Wald statistic for testing logistic regression models based on case-control data. Sci. China Ser. A-Math. 51, 2020–2032 (2008). https://doi.org/10.1007/s11425-008-0086-z

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  • DOI: https://doi.org/10.1007/s11425-008-0086-z

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