A CORRELATION GOODNESS-OF-FIT TEST FOR RANDOMLY CENSORED-DATA
成果类型：
Article
署名作者：
CHEN, CH
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1984
页码：
315322
关键词：
摘要：
For testing a composite goodness-of-fit hypothesis with randomly censored data, a correlation statistic which is an analog of the Shapiro-Francia statistic is presented. The test for exponentiality, in case of light censoring, is asymptotically robust against departures from the Koziol-Green model of random censorship. The power of the test is compared with the total-time-on-test procedure and the new-better-than-used test using Monte Carlo simulation. As an example, the test is applied to some data with prostate cancer.