It is common practice to use Cox-Snell residuals to check for overall goodness of tin survival models. We evaluate the presumed relation of unit exponentially dis-tributed residuals for a good model t and evaluate under some violations of themodel. This is done graphically with the usual graphs of Cox-Snell residual andformally using Kolmogorov-Smirnov goodness of t test. It is observed that residu-als from a correctly tted model follow unit exponential distribution. However, theCox-Snell residuals do not seem to be sensitive to the violations of the model.

Time-to-event data is used in this thesis to analyze private cars’ longevity in Sweden. Thedataset is provided by Trafikanalys and contains all registered, deregistered or temporary deregisteredcars in Sweden during the time period 2000 - 2012.A Cox proportional hazards model is fitted, including variables such as car manufacturer andcar body. The results show that directly imported cars have a much shorter median survivalcompared to non-imported cars. The convertible cars have the longest median survival amongthe five different car bodies. Sedan and station wagon body types have the shortest mediansurvival. Volvo and Mercedes have the longest survival while Renault, Ford and Opel have theshortest survival. The model fits the data reasonably well, and the assumption of proportionalhazards holds for most of the variables.

Thesis (Ph. D.)--University of Washington, 1989. / Vita. Includes bibliographical references ([217]-228).

Thesis (Ph. D.)--University of Washington, 1992. / Vita. Includes bibliographical references (leaves [135]-138).

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 97-102).

PROPHAZ is a computer program created for the analysis of survival data using the general proportional hazards model. It was designed specifically for the situation in which the underlying hazard function may be estimated from the mortality experience of a large reference population, but may be used for other problems as well. Input for the program includes the variables of interest as well as the information necessary for estimating the hazard function (demographic and mortality data). Regression coefficients for the variables of interest are obtained iteratively using the Newton-Raphson method. Utilizing large sample asymptotic theory, χ2 statistics are derived which may be used to test hypotheses of the form Cβ = 0. Input format is completely flexible for the variables of interest as well as the mortality data.

No description available.

No description available.

The Cox proportional hazards model is a standard tool for modelling the effect of covariates on time to event in the presence of censoring. The appropriateness of this model is conditioned by the validity of the proportional hazards assumption. The assumption is explained in the thesis and methods for its testing are described in detail. The tests are implemented in R, including self-written version of the Lin- Zhang-Davidian test. Their application is illustrated on medical data. The ability of the tests to reveal the violation of the proportional hazards assumption is investigated in a simulation study. The results suggest that the highest power is attained by the newly implemented Lin-Zhang-Davidian test in most cases. In contrast, the weighted version of the Lin-Wei-Ying test was found to have inadequate size for low sample sizes.

The two and k-sample tests of equality of the survival distributions against the alternatives including cross-effects of survival functions, proportional and monotone hazard ratios, are given for the right censored data. The asymptotic power against approaching alternatives is investigated. The tests are applied to the well known chemio and radio therapy data of the Gastrointestinal Tumor Study Group. The P-values for both proposed tests are much smaller then in the case of other known tests. Differently from the test of Stablein and Koutrouvelis the new tests can be applied not only for singly but also to randomly censored data.