Petoussis, Kos and Gill, Richard and Zeelenberg, Kees (1997): Statistical analysis of heaped duration data.

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Abstract
This paper shows how heaping of duration data, e.g. caused by rounding due to memory effects, can be analyzed. If the data are heaped Cox's partial likelihood approach, which is often used in survival analysis, is no longer appropriate. We show how this problem can be overcome by considering the problem as a missing data problem. A variant of Cox's Proportional Hazard Model is constructed that takes heaping into account, and is estimated by maximum likelihood using the EM algorithm, with many nuisance parameters, simultaneously for all parameters. Ingredients of our method are application of the EM algorithm, Cox regression and nonparametric maximum likelihood calculation with `predicted' data in each M step. An example from practice, where jackknife is used to estimate the variances, illustrates the power of the new methodology.
Item Type:  MPRA Paper 

Original Title:  Statistical analysis of heaped duration data 
English Title:  Statistical analysis of heaped duration data 
Language:  English 
Keywords:  heaping; duration data; survival analysis; Proportional Hazard Model; profile likelihood; EM algorithm 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C23  Panel Data Models ; Spatiotemporal Models C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C41  Duration Analysis ; Optimal Timing Strategies J  Labor and Demographic Economics > J6  Mobility, Unemployment, Vacancies, and Immigrant Workers > J64  Unemployment: Models, Duration, Incidence, and Job Search 
Item ID:  89263 
Depositing User:  Kees Zeelenberg 
Date Deposited:  03 Oct 2018 16:22 
Last Modified:  03 Oct 2019 17:52 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/89263 