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Assessing the Fit of the Logistic Model: A Case Study of Children with the Haemolytic Uraemic Syndrome

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  • Richard Kay
  • Sarah Little

Abstract

Regression methods for binary data are frequently based on the logistic model. There has been a considerable amount of very recent work concerned with methods for assessing the fit of this model to data. The purpose of this paper is to illustrate the application of these developments in model choice and assessment in terms of a case study of seventy‐five children with the haemolytic‐uraemic syndrome.

Suggested Citation

  • Richard Kay & Sarah Little, 1986. "Assessing the Fit of the Logistic Model: A Case Study of Children with the Haemolytic Uraemic Syndrome," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(1), pages 16-30, March.
    • Handle: RePEc:bla:jorssc:v:35:y:1986:i:1:p:16-30
    DOI: 10.2307/2347860
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    Cited by:

    1. William Greene, 2007. "Discrete Choice Modeling," Working Papers 07-6, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Kaili Wang & Sanjana Hossain & Khandker Nurul Habib, 2022. "A hybrid data fusion methodology for household travel surveys to reduce proxy biases and under-representation of specific sub-group of population," Transportation, Springer, vol. 49(6), pages 1801-1836, December.
    3. Jayne M. Godfrey, 1994. "Foreign Currency Accounting Policy: The Impact of Asset Specificity," Contemporary Accounting Research, John Wiley & Sons, vol. 10(2), pages 643-671, March.
    4. Kazutaka Kurasawa, 2017. "Forecasting US recession with the economic policy uncertainty indexes of policy categories," Economics and Business Letters, Oviedo University Press, vol. 6(4), pages 100-109.

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