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
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 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.
Fleming’s Two-Stage Design: A Worked Example
A computational guide to Fleming