Frailty Models for Clustered Survival Data
A practical guide to frailty models for clustered survival data, including shared frailty, gamma frailty, log-normal frailty, hazard interpretation, within-cluster dependence, estimation, model diagnostics, R implementation, and a clinical trial worked example.
Cure Models for Long-Term Survivors
A practical guide to cure models for long-term survivors, including mixture cure models, cure fractions, latency distributions, likelihood-based estimation, interpretation, diagnostics, and R implementation.
Cox Regression with Stratified Baseline Hazards
A practical guide to stratified Cox proportional hazards regression, including stratum-specific baseline hazards, the stratified partial likelihood, interpretation, SAS and R implementation, proportional-hazards diagnostics, and a worked clinical-trial example.
Accelerated Failure Time Models Explained
A practical guide to accelerated failure time models for clinical survival analysis, including the AFT interpretation, survival-time ratios, Weibull and log-normal models, censoring, model fitting in R, interpretation, diagnostics, and a complete worked example.
Parametric Survival Models: Weibull and Exponential
A deep, formula-by-formula guide to parametric survival models: the exponential and Weibull distributions with every parameter explained explicitly, both the proportional hazards and accelerated failure time parametrizations fit on the same data, and their exact algebraic relationship verified numerically.
Kaplan-Meier Survival Curves Explained
A deep, computationally grounded guide to the Kaplan-Meier estimator: the product-limit method derived from first principles, a real hand-worked example, Greenwood confidence bands, a validated log-rank test, and restricted mean survival time as an alternative to the hazard ratio.
Cox Proportional Hazards: Model Diagnostics
A deep, computationally grounded guide to the Cox proportional hazards model: the partial likelihood derived from first principles, a real Newton-Raphson fit, the exact log-rank/score-test equivalence, Breslow vs Efron tie handling, Schoenfeld residuals, and a genuine non-proportional-hazards worked example.
Competing Risks Analysis in Clinical Trials
A deep, computationally grounded guide to competing risks: the real bias from treating competing events as censoring, the Aalen-Johansen cumulative incidence function, and cause-specific vs. Fine-Gray subdistribution hazard models implemented and compared from scratch.