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Estimation in Hazard Regression Models under Ordered Departures from Proportionality

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Author Info
Bhattacharjee, A.

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Abstract

Notions of monotone ordering with respect to continuous covariates in duration data regression models have recently been discussed, and tests for the proportional hazards model against such alternatives have been developed (Bhattacharjee and Das, 2002). Such monotone/ ordered departures are common in applications, and provide useful additional information about the nature of covariate dependence. In this paper, we describe methods for estimating hazard regression models when such monotone departures are known to hold. In particular, it is shown how the histogram sieve estimators (Murphy and Sen, 1991) in this setup can be smoothed and order restricted estimation performed using biased bootstrap techniques like adaptive bandwidth kernel estimators (Brockmann et. al., 1993; Schucany, 1995) or data tilting (Hall and Huang, 2001). The performance of the methods is compared using simulated data, and their use is illustrated with applications from biomedicine and economic duration data.

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Publisher Info
Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0337.

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Length: 26
Date of creation: Feb 2003
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Handle: RePEc:cam:camdae:0337

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Related research
Keywords: Proportional hazards; Ordered restricted inference; Age-varying covariate effects; Biased bootstrap; Data tilting; Adaptive bandwidth selection; Histogram sieve estimator;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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  1. Arnab Bhattacharjee, 2007. "A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models," Discussion Paper Series, Department of Economics 0708, Department of Economics, University of St. Andrews. [Downloadable!]
    Other versions:
  2. Arnab Bhattacharjee, 2008. "Partial Orders with Respect to Continuous Covariates and Tests for the Proportional Hazards Model," Discussion Paper Series, Department of Economics 0807, Department of Economics, University of St. Andrews. [Downloadable!]
  3. Arnab Bhattacharjee, 2005. "Models of Firm Dynamics and the Hazard Rate of Exits: Reconciling Theory and Evidence using Hazard Regression Models," Econometrics 0503021, EconWPA. [Downloadable!]
    Other versions:
  4. Arnab Bhattacharjee & Madhuchhanda Bhattacharjee, 2007. "Bayesian Analysis of Hazard Regression Models under Order Restrictions on Covariate Effects and Ageing," Discussion Paper Series, Department of Economics 0707, Department of Economics, University of St. Andrews. [Downloadable!]
    Other versions:
  5. Bhattacharjee, A. & Higson, C. & Holly, S. & Kattuman, P., 2004. "Business Failure in UK and US Quoted Firms: Impact of Macroeconomic Instability and the Role of Legal Institutions," Cambridge Working Papers in Economics 0420, Faculty of Economics, University of Cambridge. [Downloadable!]
  6. Arnab Bhattacharjee, 2009. "Testing for Proportional Hazards with Unrestricted Univariate Unobserved Heterogeneity," Discussion Paper Series, Department of Economics 0904, Department of Economics, University of St. Andrews. [Downloadable!]
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This page was last updated on 2010-1-27.

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