We consider the competing-risks problem without making any assumption concerning the independence of the risks. Maximum-likelihood estimates of the cause-specific hazard rates are obtained under the condition that their ratio is monotone. We also consider the likelihood-ratio test for testing the proportionality of two cause-specific hazard rates against the alternative that the ratio of these two hazard rates is monotonic. This testing problem is equivalent to testing independence against likelihood-ratio dependence of the time to failure and the cause of failure in the competing-risks setup. We allow for random censoring on the night. The asymptotic null distribution of the test statistic is obtained and is found to be of the chi-bar-square type. The problem is extended to the case of more than two risks. A numerical example is given to illustrate the procedure.
机构:
Department of Statistics, Cochin University of Science and Technology, CochinStat Math Unit, Indian Statistical Institute, SJS Sansanwal Maarg
Sankaran P.G.
Anisha P.
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Department of Statistics, Cochin University of Science and Technology, Cochin
Indian Statistical Institute, ChennaiStat Math Unit, Indian Statistical Institute, SJS Sansanwal Maarg
机构:
Huaqiao Univ, Sch Math Sci, Quanzhou 362021, Peoples R ChinaHuaqiao Univ, Sch Math Sci, Quanzhou 362021, Peoples R China
Qiu, Zhiping
Wan, Alan T. K.
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City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R ChinaHuaqiao Univ, Sch Math Sci, Quanzhou 362021, Peoples R China
Wan, Alan T. K.
Zhou, Yong
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Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China
Chinese Acad Sci, Beijing, Peoples R ChinaHuaqiao Univ, Sch Math Sci, Quanzhou 362021, Peoples R China
Zhou, Yong
Gilbert, Peter B.
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Univ Washington, Dept Biostat, Seattle, WA 98109 USA
Fred Hutchinson Canc Res Ctr, 1124 Columbia St, Seattle, WA 98104 USAHuaqiao Univ, Sch Math Sci, Quanzhou 362021, Peoples R China