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Dealing with the Phenomenon of Quasi-complete Separation and a Goodness of Fit Test in Logistic Regression Models in the Case of Long Data Sets

Author

Listed:
  • V. G. Vassiliadis

    (Democritus University of Thrace)

  • I. I. Spyroglou

    (Democritus University of Thrace)

  • A. G. Rigas

    (Democritus University of Thrace)

  • J. R. Rosenberg

    (University of Glasgow)

  • K. A. Lindsay

    (University of Glasgow)

Abstract

The phenomenon of quasi-complete separation that appears in the identification of the neuromuscular system called muscle spindle by a logistic regression model is considered. The system responds when it is affected by a number of stimuli. Both the response and the stimuli are very long binary sequences of events. In the logistic model, three functions are of special interest: the threshold, the recovery and the summation functions. The maximum likelihood estimates are obtained efficiently and very fast by using the penalized likelihood function. A validity test for the fitted model based on the randomized quantile residuals is proposed. The validity test is transformed to a goodness of fit test and the use of Q–Q plot is also discussed.

Suggested Citation

  • V. G. Vassiliadis & I. I. Spyroglou & A. G. Rigas & J. R. Rosenberg & K. A. Lindsay, 2019. "Dealing with the Phenomenon of Quasi-complete Separation and a Goodness of Fit Test in Logistic Regression Models in the Case of Long Data Sets," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 567-596, December.
    • Handle: RePEc:spr:stabio:v:11:y:2019:i:3:d:10.1007_s12561-019-09249-z
    DOI: 10.1007/s12561-019-09249-z
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    1. D. J. Venzon & S. H. Moolgavkar, 1988. "A Method for Computing Profile‐Likelihood‐Based Confidence Intervals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(1), pages 87-94, March.
    2. Carter, David B. & Signorino, Curtis S., 2010. "Back to the Future: Modeling Time Dependence in Binary Data," Political Analysis, Cambridge University Press, vol. 18(3), pages 271-292, July.
    3. Liang, Jiajuan & Tang, Man-Lai & Chan, Ping Shing, 2009. "A generalized Shapiro-Wilk W statistic for testing high-dimensional normality," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3883-3891, September.
    4. Karavasilis, G.J. & Kotti, V.K. & Tsitsis, D.S. & Vassiliadis, V.G. & Rigas, A.G., 2005. "Statistical methods and software for risk assessment: applications to a neurophysiological data set," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 243-263, April.
    5. Dimitrios Tsitsis & George Karavasilis & Alexandros Rigas, 2012. "Measuring the association of stationary point processes using spectral analysis techniques," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 23-47, March.
    6. Zorn, Christopher, 2005. "A Solution to Separation in Binary Response Models," Political Analysis, Cambridge University Press, vol. 13(2), pages 157-170, April.
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