scholarly journals Hierarchical likelihood inference on clustered competing risks data

2015 ◽  
Vol 35 (2) ◽  
pp. 251-267 ◽  
Author(s):  
Nicholas J. Christian ◽  
Il Do Ha ◽  
Jong-Hyeon Jeong
Keyword(s):  
Competing Risks ◽  
Likelihood Inference ◽  
Hierarchical Likelihood ◽  
Competing Risks Data

scholarly journals Parametric likelihood inference for interval censored competing risks data

Biometrics ◽  
2014 ◽  
Vol 70 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Michael G. Hudgens ◽  
Chenxi Li ◽  
Jason P. Fine
Keyword(s):  
Competing Risks ◽  
Likelihood Inference ◽  
Interval Censored ◽  
Competing Risks Data

scholarly journals Modeling semi‐competing risks data as a longitudinal bivariate process

Biometrics ◽  
2021 ◽  
Author(s):  
Daniel Nevo ◽  
Deborah Blacker ◽  
Eric B. Larson ◽  
Sebastien Haneuse
Keyword(s):  
Competing Risks ◽  
Competing Risks Data

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.

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