
Abstract
In this paper a semiparametric hazard model introduced by Cox (1972) is used to model transitions intensities for a long term care (LTC) data set. The main focus is the inclusion of the diagnoses which led to LTC as explanatory variables. Modern model diagnostic techniques are applied to check the model assumptions. Fractional Polynomials proposed by Royston and Altman (1994) are used to model the functional form of continuous covariates. Time dependency is examined graphically by using scaled Schoenfeld residuals (see Grambsch and Therneau(1994)). It is shown that the inclusion of diagnoses significantly improves the estimated transition probabilities on which premiums are based. As an alternative approach a piecewise exponential model is fitted and compared to the semiparametric hazard model.
Item Type: | Paper |
---|---|
Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1680-1 |
Language: | English |
Item ID: | 1680 |
Date Deposited: | 05. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |