Information criteria for Firth's penalized partial likelihood approach in Cox regression models.

ABSTRACT: In the estimation of Cox regression models, maximum partial likelihood estimates might be infinite in a monotone likelihood setting, where partial likelihood converges to a finite value and parameter estimates converge to infinite values. To address monotone likelihood, previous studies have applied Firth's bias correction method to Cox regression models. However, while the model selection criteria for Firth's penalized partial likelihood approach have not yet been studied, a heuristic AIC-type information criterion can be used in a statistical package. Application of the heuristic information criterion to data obtained from a prospective observational study of patients with multiple brain metastases indicated that the heuristic information criterion selects models with many parameters and

SUBMITTER: Nagashima K 

PROVIDER: S-EPMC6084330 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature