UW Biiostatistics & Medical Informatics UW Biostatistics & Medical Informatics UW Madison UW Biostatistics & Medical Informatics Site Map
UW School of Medicine and Public Health UW Madison



Other Seminar Series


General Departmental Seminar Series

Rank Tests for Clustered Survival Data

Sin-Ho Jung, Division of Biostatistics
Indiana University School of Medicine

Friday, Dec 1, 2000, 12:00-1:00 pm

G5/136-142 Clinical Sciences Center, 600 Highland Avenue


In a clinical trial, we may randomize subjects (called clusters) to different treatments, and make observations from multiple sites (called units) of each subject. In this case, the observations within each subject could be dependent, whereas those from different subjects are independent. If the outcome of interest is the time to an event, we may use the standard rank tests proposed for independent survival data, such as the logrank and Wilcoxon tests, to test the equality of marginal survival distributions, but their standard error should be modified to accommodate the possible intracluster correlation. In this paper we propose a method of calculating the standard error of the rank tests for two-sample clustered survival data. The method is naturally extended to that for K-sample tests under dependence.

Back to General Departmental Seminar Series


Internal Use | Site Map | Search |
Overview | People | Training | Research | Seminars | Employment | Links |
Biostatistics Program | Clinical Trials Program | Medical Informatics Program | Biomedical Computing |

Copyright © 2006 The Board of Regents of the
University of Wisconsin System


UW Madison UW School of Medicine and Public Health