Sample Size for Bioequivalence Studies
A detailed guide to sample size planning for bioequivalence studies, including crossover designs, intra-subject variability, geometric mean ratios, 80–125% acceptance limits, power, dropout, and worked examples.
Sample Size Re-Estimation Methods
A practical guide to sample size re-estimation in clinical trials, including blinded and unblinded re-estimation, nuisance parameter adjustment, internal pilot designs, conditional power, promising-zone methods, type I error control, worked examples, and R implementation.
Sample Size Considerations for Pilot Studies
A practical guide to sample size planning for pilot studies, including feasibility objectives, estimation, precision, progression criteria, recruitment, retention, variance estimation, event rates, and when formal power calculations are appropriate.
Response-Adaptive Randomization
A practical guide to response-adaptive randomization in clinical trials, including the basic concept, allocation probabilities, Bayesian response-adaptive randomization, ethical and statistical considerations, a complete worked example, and common pitfalls.
Real-World Evidence in Regulatory Submissions
A practical guide to using real-world data and real-world evidence in regulatory submissions, including regulatory questions, data fitness, study design, target trial emulation, confounding, missing data, causal inference, transportability, FDA and EMA expectations, submission documentation, and R implementation.
ROC Curve Analysis Explained
A practical guide to ROC curve analysis, including sensitivity, specificity, thresholds, AUC, Youden
Platform Trials Explained
A comprehensive guide to platform trials, including master protocols, shared control groups, treatment-arm entry and removal, interim analyses, adaptive randomization, statistical multiplicity, operating characteristics, Bayesian and frequentist approaches, and a complete worked example.
Non-Inferiority Trial Design Principles
A practical guide to non-inferiority trial design, including the non-inferiority margin, hypotheses, confidence intervals, assay sensitivity, constancy assumptions, sample size, analysis populations, missing data, and a complete worked example.
Multiplicity Guidance from FDA and EMA
A practical guide to FDA and EMA expectations for multiplicity in clinical trials, including Type I error control, multiple primary endpoints, hierarchical testing, gatekeeping, alpha recycling, subgroup analyses, interim analyses, confidence intervals, estimands, SAP planning, and R implementation.
Master Protocols in Clinical Research
A comprehensive guide to master protocols in clinical research, including umbrella, basket, platform, and multi-arm multi-stage designs, shared controls, statistical multiplicity, adaptations, estimands, operational considerations, and worked examples.