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Scaled Fisher Consistency of the Partial Likelihood Estimator in the Cox Model with Arbitrary Frailty

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Języki publikacji
EN
Abstrakty
EN
It is argued that inference based on the Cox regression model and the partial likelihood estimator is possible for various extensions of the model, which in particular include an arbitrary frailty variable. We demonstrate that the estimator in such a general setup is Fisher consistent up to a scaling factor under symmetry type distributional assumptions on explanatory variables. A simulation experiment shows exemplary behaviour of the estimator and also of a test of fit based on the Anderson–Darling statistic for different Cox model extensions.
Słowa kluczowe
Rocznik
Strony
77--87
Opis fizyczny
Bibliogr. 15 poz., tab., wykr.
Twórcy
  • Institute of Economic Sciences, University of Wrocław, Faculty of Law, Administration and Economics, Uniwersytecka 22/26, 50-145 Wrocław, Poland
  • Institute of Economic Sciences, University of Wrocław, Faculty of Law, Administration and Economics, Uniwersytecka 22/26, 50-145 Wrocław, Poland
Bibliografia
  • [1] O. O. Aalen, Modelling heterogeneity in survival analysis by the compound Poisson distribution, Ann. Appl. Probab. 4 (1992), 951-972.
  • [2] O. O. Aalen, O. Borgan, and H. K. Gjessing, Survival and Event History Analysis: A Process Point of View, Springer, New York, 2008.
  • [3] I. Baltazar-Aban and E. A. Peña, Properties of hazard-based residuals and implications in model diagnostics, J. Amer. Statist. Assoc. 90 (1995), 185-197.
  • [4] T. Bednarski, Robust estimation in Cox’s regression model, Scand. J. Statist. 20 (1993), 213-225.
  • [5] T. Bednarski, and M. Skolimowska-Kulig, Scaled consistent estimation of regression parameters in frailty models, Acta Univ. Lodziensis Folia Oeconomica 5(338) (2018), 133-142.
  • [6] T. Bednarski and N. Skolimowska-Kulig, On scale Fisher consistency of maximum likelihood estimator for the exponential regression model under arbitrary frailty, Statist. Probab. Lett. 150 (2019), 9-12.
  • [7] D. R. Cox, Regression models and life-tables (with discussion), J. Roy. Statist. Soc. B 34 (1972), 187-220.
  • [8] R. Henderson and P. Oman, Effect of frailty on marginal regression estimates in survival analysis, J. Roy. Statist. Soc. B 61 (1999), 367-379.
  • [9] R. A. Marona, R. D. Martin, and V. J. Yohai, Robust Statistics: Theory and Methods, Wiley, 2006.
  • [10] S. A. Murphy, Consistency in a proportional hazard model incorporating a random effect, Ann. Statist. 22 (1994), 712-734.
  • [11] P. Ruud, Sufficient conditions for the consistency of maximum likelihood estimation despite misspecification of distribution in multinomial discrete choice models, Econometrica 51 (1983), 225-228.
  • [12] P. D. Sasieni, Maximum weighted partial estimates for Cox model, J. Amer. Statist. Assoc. 88 (1993), 144-152.
  • [13] T. Stoker, Consistent estimation of scaled coefficients, Econometrica 54 (1986), 1461-1481.
  • [14] J. W. Vaupel, K. G. Manton, and E. Stallard, The impact of heterogeneity in individual frailty on the dynamics of mortality, Demography 16 (1979), 439-454.
  • [15] A. Wienke, Frailty Models in Survival Analysis, Chapman and Hall, 2011.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-98df8df0-bbf4-4957-9790-2f08eafc1c02
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