Statistical Analysis of Multivariate Interval-Censored Data in Breast Cancer Follow-Up Studies

2000 ◽  
Author(s):  
George Wong
Keyword(s):  
Breast Cancer ◽  
Statistical Analysis ◽  
Censored Data ◽  
Interval Censored Data ◽  
Follow Up Studies ◽  
Interval Censored

Statistical analysis of bivariate interval-censored failure time data

2015 ◽  
Author(s):  
◽  
Qingning Zhou
Keyword(s):  
Statistical Analysis ◽  
Censored Data ◽  
Failure Time ◽  
Current Status Data ◽  
Current Status ◽  
Interval Censored Data ◽  
Time Data ◽  
Failure Times ◽  
Interval Censored ◽  
Status Data

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Interval-censored failure time data arise when the failure time of interest in a survival study is not exactly observed but known only to fall within some interval. One area that often produces such data is medical studies with periodic follow-ups, in which the medical condition of interest such as the onset of a disease is only known to occur between two adjacent examination times. An important special case of intervalcensored data is current status data which arise when each study subject is observed only once and the only information available is whether the failure event of interest has occurred or not by the observation time. The areas that often yield such data include tumorigenicity experiments and cross-sectional studies. Sometimes we refer to current status data as case I interval-censored data, and the general case as case II interval-censored data. The analysis of both case I and case II interval-censored data has recently attracted a great deal of attention and many procedures have been proposed for various issues related to it. However, there are still a number of problems that remain unsolved or lack approaches that are simpler, more efficient and apply to more general situations compared to the existing ones. This is especially the case for multivariate intervalcensored data which arise if there are multiple failure times of interest and all of them suffer intervalcensoring. This dissertation focuses on the statistical analysis for bivariate interval-censored data, including regression analysis, model selection and estimation of the association between failure times.

Process and statistical analysis of interval censored data in HPM effect experiment

2013 ◽  
Vol 25 (9) ◽  
pp. 2351-2354
Author(s):  
陆希成 Lu Xicheng ◽  
韩峰 Han Feng ◽  
刘钰 Liu Yu ◽  
江凌 Jiang Ling ◽  
杨志强 Yang Zhiqiang
Keyword(s):  
Statistical Analysis ◽  
Censored Data ◽  
Interval Censored Data ◽  
Interval Censored ◽  
Effect Experiment
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