Conditional Proportional Hazards Models
Bivariate survival models can sometimes be characterized in terms of conditional survival functions of the form P(X > x|Y > y) and P(Y > y|X > x). Attention is focussed on models in which these conditional survival functions are of the proportional hazards form. A characterization of such distributions is provided and related estimation problems are discussed.
KeywordsSurvival Function Conditional Density Conditional Survival Generalize Likelihood Ratio Test Bivariate Survival
Unable to display preview. Download preview PDF.
- Arnold, B.C. (1974). Conditional survival models. To appear as Chapter 31 in Recent Advances in Life-testing and Reliability, CRC Press, Boca Raton, Florida.Google Scholar
- Arnold, B.C., E. Castillo and J. M. Sarabia (1992). Conditionally specified distributions. Lecture Notes in Statistics #73, Springer, Berlin.Google Scholar
- Cox, D. R. and Oakes, D. (1984). Analysis of Survival Data. Chapman Hall, London.Google Scholar
- Narumi, S. (1923). “On the general forms of bivariate frequency distributions which are mathematically possible when regression and variation are subjected to limiting conditions I and II,” Biometrika, 15, 77–88, 209–21.Google Scholar