CoxPhLb

CoxPhLb implements semiparametric Cox proportional hazards analysis for length-biased (left-truncated under the stationarity assumption) survival data to estimate covariate effects and assess model assumptions.

Key Features:

• R package: Implemented in R for analysis of length-biased survival data.
• Semiparametric Cox model: Implements semiparametric regression methods tailored for length-biased data under the Cox proportional hazards model.
• Exploration of covariate effects: Fits the Cox model to estimate associations between covariates and survival times in length-biased samples.
• Proportional hazards assumption checking: Includes functionality to verify the proportional hazards assumption for fitted models.
• Stationarity assumption checking: Includes functionality to assess the stationarity assumption required for length-biased sampling.

Scientific Applications:

• Epidemiology: Analysis of prevalent cohort studies subject to length-biased sampling to estimate survival associations.
• Medical research: Modeling survival outcomes and covariate effects in clinical and observational datasets affected by length bias.
• Method demonstration and evaluation: Applied to simulated datasets and real-world data such as the Channing House dataset for demonstration and evaluation.

Methodology:

Implements semiparametric Cox proportional hazards regression methods developed for handling length-biased (left-truncated under stationarity) survival data.