It has been almost sixty years since Kolmogorov introduced a distribution-free test for the simple null hypothesis that a distribution function coincides with a given distribution function. In 1949 Doob observed that Kolmogorov's approach could be simplified by transforming the empirical process to an empirical process based on uniform random variables. In recent years this approach has led to the construction of distribution-free tests when unknown parameters are present. The purpose of this dissertation is to apply the transformation approach in the setting of survival analysis, where censoring and covariate information further complicate the problem. Asymptotic distribution-free tests are developed for testing independence of a survival time from a covariate, and for checking the adequacy of Cox's proportional hazards model. The test statistics are obtained from certain test statistic processes (indexed by time and covariate) which converge in distribution to Brownian sheets. A simulation study is carried out to investigate the finite sample properties of the proposed tests and they are applied to data from the British Medical Research Council's (1984) 4th myelomatosis trial. / Source: Dissertation Abstracts International, Volume: 53-11, Section: B, page: 5805. / Major Professor: Ian McKeague. / Thesis (Ph.D.)--The Florida State University, 1992.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76821 |
| Contributors | Sun, Yanqing., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 88 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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