title: Cause-Specific Hazard Regression for Competing Risks Data Under Interval Censoring and Left Truncation.
abstract: 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.
authors.affiliation: Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, U.S.A.
authors.forename: Chenxi
authors.initials: C
authors.lastname: Li
keywords: Cause-specific hazard; Competing risks; Interval censoring; Left truncation; Penalized likelihood; Smoothing parameter selection