Generalized rank tests for univariate and bivariate interval-censored failure time data
碩士 === 國立中山大學 === 應用數學系研究所 === 91 === In Part 1 of this paper, we adapt Turnbull’s algorithm to estimate the distribution function of univariate interval-censored and truncated failure time data. We also propose four non-parametric tests to test whether two groups of the data come from the same dist...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2003
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| Online Access: | http://ndltd.ncl.edu.tw/handle/66877955733235934635 |
| Summary: | 碩士 === 國立中山大學 === 應用數學系研究所 === 91 === In Part 1 of this paper, we adapt Turnbull’s algorithm to estimate the distribution function of univariate interval-censored and truncated
failure time data. We also propose four non-parametric tests to test whether two groups of the data come from the same distribution. The
powers of proposed test statistics are compared by simulation under different distributions. The proposed tests are then used to analyze an AIDS study.
In Part 2, for bivariate interval-censored data, we propose some models of how to generate the data and several methods to measure the
correlation between the two variates. We also propose several nonparametric tests to determine whether the two variates are mutually independent or whether they have the same distribution. We demonstrate the performance of these tests by simulation and give an application to AIDS study（ACTG 181）.
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