Statistical Considerations for Rare Disease Trials
A practical guide to statistical considerations for rare disease clinical trials, including small sample sizes, endpoint selection, natural history, external controls, randomization, Bayesian methods, adaptive designs, missing data, multiplicity, estimands, and regulatory considerations.
Spider Plots for Tumor Response
A practical guide to spider plots for tumor response in oncology clinical trials, including longitudinal tumor burden, percent change from baseline, RECIST 1.1 response thresholds, patient trajectories, progressive disease, partial response, complete response, data preparation, interpretation, and R implementation.
Simon’s Two-Stage Design: A Worked Example
A practical and computational guide to Simon’s two-stage design for single-arm oncology trials, including early stopping for futility, type I error, power, expected sample size, a complete worked example, and implementation in R.
Shift Tables for Laboratory Data
A practical guide to shift tables for laboratory data in clinical trials, including baseline-to-post-baseline changes, CTCAE grading, treatment-emergent abnormalities, denominator selection, interpretation, QC, and R implementation.
Seamless Phase II/III Adaptive Designs
A comprehensive guide to seamless Phase II/III adaptive clinical trial designs, including treatment selection, sample size adaptation, endpoint continuity, type I error control, combination of Phase II and Phase III stages, conditional power, and worked examples.
Sample Size for Repeated Measures Designs
A computationally grounded guide to sample size planning for repeated measures and longitudinal clinical trials, including within-subject correlation, effect sizes, repeated measures ANOVA, mixed models, attrition, nonsphericity, and worked sample size calculations.
Sample Size for Odds Ratios in Case-Control Studies
A computational guide to sample size planning for case-control studies using odds ratios, exposure prevalence, statistical power, significance level, case-control ratios, and worked examples.
Sample Size for Diagnostic Accuracy Studies
A computational guide to sample size planning for diagnostic accuracy studies, including sensitivity, specificity, prevalence, confidence interval precision, expected diseased and non-diseased subjects, verification, and practical clinical trial considerations.
Sample Size for Count/Poisson Outcomes
A computational guide to sample size planning for count and Poisson outcomes, including event rates, person-time, rate ratios, exposure time, unequal follow-up, overdispersion, negative binomial models, and complete worked examples.
Sample Size for Correlation and Regression Studies
A computational guide to sample size planning for correlation and regression studies, including Pearson correlation, Fisher