Sample Size for Non-Inferiority Trials
A practical guide to sample size calculation for non-inferiority clinical trials, including non-inferiority margins, one-sided type I error, power, continuous and binary endpoints, dropout inflation, worked examples, formulas, and R implementation.
Sample Size for Equivalence Trials
A practical guide to sample size determination for equivalence trials, including equivalence margins, the two one-sided tests procedure, continuous and binary endpoints, power, dropout inflation, a complete worked example, and R implementation.
Sample Size for Cluster Randomized Trials
A practical guide to sample size calculation for cluster randomized trials, including the intracluster correlation coefficient, design effect, cluster size, inflation for clustering, attrition, number of clusters, and a complete worked example.
Sample Size Re-Estimation in Adaptive Trials
A practical guide to sample size re-estimation in adaptive clinical trials, including blinded and unblinded re-estimation, nuisance parameter adjustment, conditional power, type I error control, decision rules, and a complete worked example.
SAS Macros for Clinical Table Generation
A practical guide to building reusable SAS macros for clinical table generation, including macro parameters, dynamic titles and footnotes, treatment columns, statistical summaries, PROC REPORT integration, validation, and a complete adverse-event table example.
Robust Regression Methods for Clinical Data
A practical guide to robust regression methods for clinical data, including Huber and MM estimation, influence diagnostics, robust standard errors, quantile regression, clinical sensitivity analyses, and R and SAS implementation.
Ridge and Lasso Regression in Biostatistics
A practical guide to ridge and lasso regression in biostatistics, including penalized regression, multicollinearity, variable selection, cross-validation, interpretation, and worked R examples.
Restricted Mean Survival Time (RMST)
A practical guide to Restricted Mean Survival Time (RMST), including the RMST definition, Kaplan-Meier integration, RMST difference and ratio, interpretation, hypothesis testing, confidence intervals, clinical trial applications, R implementation, and worked examples.
Reference-Based Multiple Imputation Methods
A practical guide to reference-based multiple imputation methods for clinical trials, including jump to reference, copy increments in reference, copy reference, assumptions, implementation, Rubin
Random Slopes vs. Random Intercepts Explained
A practical guide to random intercepts and random slopes in linear mixed-effects models, including interpretation, covariance structures, model comparison, longitudinal clinical trial examples, R lme4 code, SAS PROC MIXED, and common modeling mistakes.