Statistical Methods for Conditional Survival Analysis.

TitleStatistical Methods for Conditional Survival Analysis.
Publication TypeJournal Article
Year of Publication2018
AuthorsJung, Sin-Ho, Ho Yun Lee, and Shein-Chung Chow
JournalJ Biopharm Stat
Volume28
Issue5
Pagination927-938
Date Published2018
ISSN1520-5711
KeywordsData Interpretation, Statistical, Humans, Models, Statistical, Proportional Hazards Models, Survival Analysis
Abstract

We investigate the survival distribution of the patients who have survived over a certain time period. This is called a conditional survival distribution. In this paper, we show that one-sample estimation, two-sample comparison and regression analysis of conditional survival distributions can be conducted using the regular methods for unconditional survival distributions that are provided by the standard statistical software, such as SAS and SPSS. We conduct extensive simulations to evaluate the finite sample property of these conditional survival analysis methods. We illustrate these methods with real clinical data.

DOI10.1080/10543406.2017.1405012
Alternate JournalJ Biopharm Stat
Original PublicationStatistical methods for conditional survival analysis.
PubMed ID29185865
PubMed Central IDPMC6195126
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
Project: