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Cause-specific hazard regression for competing risks data under interval censoring and left truncation
| Content Provider | Scilit |
|---|---|
| Author | Li, Chenxi |
| Copyright Year | 2016 |
| Description | Journal: Computational Statistics & Data Analysis Inference for cause-specific hazards from competing risks data under interval censoring and possible left truncation has been understudied. Aiming at this target, a penalized likelihood approach for a Cox-type proportional cause-specific hazards model is developed, and the associated asymptotic theory is discussed. Monte Carlo simulations show that the approach performs very well for moderate sample sizes. An application to a longitudinal study of dementia illustrates the practical utility of the method. In the application, the age-specific hazards of AD, other dementia and death without dementia are estimated, and risk factors of all competing risks are studied. |
| Related Links | http://europepmc.org/articles/pmc5176029?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176029/pdf |
| Ending Page | 208 |
| Page Count | 12 |
| Starting Page | 197 |
| ISSN | 01679473 |
| DOI | 10.1016/j.csda.2016.07.003 |
| Journal | Computational Statistics & Data Analysis |
| Volume Number | 104 |
| Language | English |
| Publisher | Elsevier BV |
| Publisher Date | 2016-12-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Computational Statistics & Data Analysis Statistics and Probability Cause-specific Hazard Competing Risks Interval Censoring Left Truncation Penalized Likelihood Smoothing Parameter Selection |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Statistics and Probability Computational Theory and Mathematics Computational Mathematics |
