title: Variable selection in subdistribution hazard frailty models with competing risks data.
abstract: The proportional subdistribution hazards model (i.e. Fine-Gray model) has been widely used for analyzing univariate competing risks data. Recently, this model has been extended to clustered competing risks data via frailty. To the best of our knowledge, however, there has been no literature on variable selection method for such competing risks frailty models. In this paper, we propose a simple but unified procedure via a penalized h-likelihood (HL) for variable selection of fixed effects in a general class of subdistribution hazard frailty models, in which random effects may be shared or correlated. We consider three penalty functions, least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and HL, in our variable selection procedure. We show that the proposed method can be easily implemented using a slight modification to existing h-likelihood estimation approaches. Numerical studies demonstrate that the proposed procedure using the HL penalty performs well, providing a higher probability of choosing the true model than LASSO and SCAD methods without losing prediction accuracy. The usefulness of the new method is illustrated using two actual datasets from multi-center clinical trials.
authors.affiliation: Department of Data Management, Daegu Haany University, Gyeongsan, South Korea.
authors.forename: Il Do
authors.initials: ID
authors.lastname: Ha
authors.forename: Minjung
authors.initials: M
authors.lastname: Lee
authors.forename: Seungyoung
authors.initials: S
authors.lastname: Oh
authors.forename: Jong-Hyeon
authors.initials: JH
authors.lastname: Jeong
authors.forename: Richard
authors.initials: R
authors.lastname: Sylvester
authors.forename: Youngjo
authors.initials: Y
authors.lastname: Lee
mesh_terms: D000368:Aged; D001943:Breast Neoplasms / Q000188:drug therapy; D003198:Computer Simulation; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000453:epidemiology / Q000517:prevention & control; D016016:Proportional Hazards Models; D013629:Tamoxifen / Q000627:therapeutic use; D001749:Urinary Bladder Neoplasms / Q000188:drug therapy
chemical_list: D013629:Tamoxifen
keywords: competing risks; frailty models; h-likelihood penalty function; penalized h-likelihood; subdistribution hazard; variable selection