A general semiparametric approach to inference with marker-dependent hazard rate models

We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker of covariate effects. A number of well-known models are special cases. In a counting process framewor...

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Bibliographic Details
Main Authors: Berg, Gerard J. van den (Author) , Janys, Lena (Author) , Mammen, Enno (Author) , Nielsen, Jens Perch (Author)
Format: Book/Monograph Working Paper
Language:English
Published: Uppsala IFAU, Institute for Evaluation of Labour Market and Education Policy February 29, 2016
Series:Working paper / IFAU, Institute for Evaluation of Labour Market and Education Policy 2016:3
In: Working papers (2016:3)

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Online Access:Resolving-System, kostenfrei, Volltext: http://hdl.handle.net/10419/166004
Verlag, Volltext: http://www.ifau.se/en/Research/Publications/Working-papers/2016/a-general-semiparametric-approach-to-inference-with-marker-dependent-hazard-rate-models/
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Author Notes:Gerard J. van den Berg, Lena Janys, Enno Mammen, Jens P. Nielsen
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Summary:We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker of covariate effects. A number of well-known models are special cases. In a counting process framework, a general profile likelihood estimator is developed and the parametric component of the model is shown to be asymptotically normal and efficient. The analysis improves on earlier results for special cases. Finite sample properties are investigated in simulations. The estimator is shown to work well under realistic empirical conditions. The estimator is applied to investigate the long-run relationship between birth weight and later-lite mortality using data from the Uppsala birth cohort study of individuals born in 1915–1929. The results suggest a relationship that is difficult to capture with sample parametric specifications. Moreover, its shape at higher birth weights differs across gender.
Physical Description:Online Resource