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Testing goodness-of-fit in logistic case-control studies

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  • Howard D. Bondell

Abstract

We present a goodness-of-fit test for the logistic regression model under case-control sampling. The test statistic is constructed via a discrepancy between two competing kernel density estimators of the underlying conditional distributions given case-control status. The proposed goodness-of-fit test is shown to compare very favourably with previously proposed tests for case-control sampling in terms of power. The test statistic can be easily computed as a quadratic form in the residuals from a prospective logistic regression maximum likelihood fit. In addition, the proposed test is affine invariant and has an alternative representation in terms of empirical characteristic functions. Copyright 2007, Oxford University Press.

Suggested Citation

  • Howard D. Bondell, 2007. "Testing goodness-of-fit in logistic case-control studies," Biometrika, Biometrika Trust, vol. 94(2), pages 487-495.
    • Handle: RePEc:oup:biomet:v:94:y:2007:i:2:p:487-495
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    File URL: http://hdl.handle.net/10.1093/biomet/asm033
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    Cited by:

    1. Zewei Lin & Dungang Liu, 2022. "Model diagnostics of discrete data regression: a unifying framework using functional residuals," Papers 2207.04299, arXiv.org.
    2. Geng, Pei & Sakhanenko, Lyudmila, 2016. "Parameter estimation for the logistic regression model under case-control study," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 168-177.
    3. Diao Guoqing & Ning Jing & qin jing, 2012. "Maximum Likelihood Estimation for Semiparametric Density Ratio Model," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-29, June.

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