A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models
AbstractThis paper extends commonly used tests for equality of hazard rates in a two-sample or k-sample setup to a situation where the covariate under study is continuous. In other words, we test the hypothesis that the conditional hazard rate is the same for all covariate values, against the omnibus alternative as well as more specific alternatives, when the covariate is continuous. The tests developed are particularly useful for detecting trend in the underlying conditional hazard rates or changepoint trend alternatives. Asymptotic distribution of the test statistics are established and small sample properties of the tests are studied. An application to the eÂ¤ect of aggregate Q on corporate failure in the UK shows evidence of trend in the covariate eÂ¤ect, whereas a Cox regression model failed to detect evidence of any covariate effect. Finally, we discuss an important extension to testing for proportionality of hazards in the presence of individual level frailty with arbitrary distribution.
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Bibliographic InfoPaper provided by Department of Economics, University of St. Andrews in its series Discussion Paper Series, Department of Economics with number 0708.
Date of creation: Sep 2007
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Postal: School of Economics and Finance, University of St. Andrews, Fife KY16 9AL
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Other versions of this item:
- Bhattacharjee, Arnab, 2004. "A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models," MPRA Paper 3937, University Library of Munich, Germany.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
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Discussion Paper Series, Department of Economics
0707, Department of Economics, University of St. Andrews.
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