Developing and evaluating risk prediction models with panel current status data.

ABSTRACT: Panel current status data arise frequently in biomedical studies when the occurrence of a particular clinical condition is only examined at several prescheduled visit times. Existing methods for analyzing current status data have largely focused on regression modeling based on commonly used survival models such as the proportional hazards model and the accelerated failure time model. However, these procedures have the limitations of being difficult to implement and performing sub-optimally in relatively small sample sizes. The performance of these procedures is also unclear under model misspecification. In addition, no methods currently exist to evaluate the prediction performance of estimated risk models with panel current status data. In this paper, we propose a simple estimator under a

SUBMITTER: Chan S 

PROVIDER: S-EPMC8168594 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature