Multiple Linear Regression in Clinical Research
A deep, computationally grounded guide to multiple linear regression: OLS derived in matrix form, a real fitted trial showing the precision gain from ANCOVA-style baseline adjustment, real residual diagnostics, and a genuine multicollinearity failure with exploding VIFs.
Modified Toxicity Probability Interval (mTPI) Design
A computational guide to the modified Toxicity Probability Interval (mTPI) design for dose-finding clinical trials, including the equivalence interval, Bayesian beta-binomial model, unit probability mass, dose escalation and de-escalation rules, a complete worked example, and R implementation.
Model-Assisted vs. Model-Based Dose-Finding Designs
A practical guide to model-assisted and model-based Phase I dose-finding designs, including BOIN, mTPI, Keyboard, CRM, TITE-CRM, dose-toxicity modeling, overdose control, simulation, and a worked comparison.
Mixed Models in R: lme4 and nlme
A practical and in-depth guide to mixed-effects models in R using lme4 and nlme, with clinical trial examples covering longitudinal repeated measures, random intercepts and slopes, covariance structures, treatment-by-time interactions, REML versus ML, estimated marginal means, diagnostics, convergence, missing data, and reporting.
Maximum Tolerated Dose (MTD) Determination
A practical guide to maximum tolerated dose determination in Phase I clinical trials, covering dose-limiting toxicities, the 3+3 design, dose-escalation rules, MTD definition, operating characteristics, and modern model-based approaches.
Markov Chain Monte Carlo (MCMC) for Clinical Statisticians
A practical and mathematical guide to Markov Chain Monte Carlo (MCMC) for clinical statisticians, including Bayesian posterior sampling, Metropolis-Hastings, Gibbs sampling, Hamiltonian Monte Carlo, convergence diagnostics, effective sample size, R implementation, and a complete clinical example.
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.
Introduction to Meta-Analysis in Clinical Research
A practical introduction to meta-analysis for clinical research, covering systematic review principles, effect measures, fixed-effect and random-effects models, heterogeneity, forest plots, funnel plots, publication bias, subgroup analysis, sensitivity analysis, and implementation in R.
Introduction to CDISC Standards
A practical introduction to CDISC standards for clinical trials, covering CDASH, SDTM, ADaM, Define-XML, controlled terminology, therapeutic-area standards, traceability, regulatory submissions, implementation workflows, and practical programming examples.
Introduction to Bayesian Statistics for Clinical Trials
An intuitive and computational introduction to Bayesian statistics for clinical trials, including prior distributions, likelihoods, posterior probabilities, credible intervals, Bayesian decision-making, predictive probabilities, and a complete worked example using a beta-binomial model.