Joint regression analysis for survival data in the presence of two sets of semi‐competing risks

2019 ◽  
Vol 61 (6) ◽  
pp. 1402-1416 ◽  
Author(s):  
Mengjiao Peng ◽  
Liming Xiang
Keyword(s):  
Regression Analysis ◽  
Competing Risks ◽  
Survival Data ◽  
Joint Regression Analysis

A Practical Guide to Family Studies with Lifetime Data

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Thomas H. Scheike ◽  
Klaus Kähler Holst
Keyword(s):  
Competing Risks ◽  
Survival Data ◽  
Age Of Onset ◽  
Familial Aggregation ◽  
Threshold Model ◽  
Right Censoring ◽  
Annual Review ◽  
Publication Date ◽  
Lifetime Data ◽  
Competing Risks Data

Familial aggregation refers to the fact that a particular disease may be overrepresented in some families due to genetic or environmental factors. When studying such phenomena, it is clear that one important aspect is the age of onset of the disease in question, and in addition, the data will typically be right-censored. Therefore, one must apply lifetime data methods to quantify such dependence and to separate it into different sources using polygenic modeling. Another important point is that the occurrence of a particular disease can be prevented by death—that is, competing risks—and therefore, the familial aggregation should be studied in a model that allows for both death and the occurrence of the disease. We here demonstrate how polygenic modeling can be done for both survival data and competing risks data dealing with right-censoring. The competing risks modeling that we focus on is closely related to the liability threshold model. Expected final online publication date for the Annual Review of Statistics and Its Application, Volume 9 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Regression Analysis of Survival Data

2021 ◽  
pp. 137-166
Author(s):  
Weichung Joe Shih ◽  
Joseph Aisner
Keyword(s):  
Regression Analysis ◽  
Survival Data
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