Hochberg and Hommel Procedures
A practical guide to the Hochberg and Hommel procedures for controlling the family-wise error rate in multiple hypothesis testing, including step-up testing, Simes tests, worked examples, adjusted p-values, assumptions, R implementation, and comparisons with Bonferroni and Holm.
Hierarchical Testing Strategies in Clinical Trials
A practical guide to hierarchical testing strategies in clinical trials, including fixed-sequence testing, gatekeeping procedures, multiple endpoints, familywise error control, graphical approaches, testing hierarchies, confirmatory analyses, and worked examples.
Hazard Ratio Interpretation for Clinicians
A practical guide for clinicians to interpreting hazard ratios from survival analyses, including relative hazard, confidence intervals, proportional hazards, absolute risk, Kaplan-Meier curves, nonproportional hazards, and common interpretation mistakes.
Handling Non-Linear Trajectories in Longitudinal Data
A practical guide to modeling non-linear trajectories in longitudinal clinical data using polynomial terms, splines, categorical time, piecewise models, mixed-effects models, and flexible time structures in R and SAS.
Growth Curve Modeling in Clinical Research
A practical guide to growth curve modeling in clinical research, including longitudinal trajectories, linear mixed-effects models, fixed and random effects, time-by-treatment interactions, covariance structures, model interpretation, R implementation, and clinical trial examples.
Graphical Approaches to Multiple Testing
A practical guide to graphical approaches for multiple testing in clinical trials, including weighted hypotheses, alpha allocation, transition weights, alpha recycling, gatekeeping, graphical procedures, FWER control, and a complete worked example.
Generalized Linear Models (GLMs) Overview
A practical clinical biostatistics guide to generalized linear models, covering the exponential family, link functions, logistic regression, Poisson and negative binomial models, model interpretation, estimation, diagnostics, and clinical trial applications.
Gatekeeping Procedures for Multiple Endpoints
A practical guide to gatekeeping procedures for multiple endpoints in clinical trials, including hierarchical testing, parallel gatekeeping, serial gatekeeping, graphical approaches, type I error control, power, worked examples, and implementation in R.
GEE vs. Mixed Models: When to Use Each
A practical guide to choosing between generalized estimating equations and mixed-effects models for longitudinal and clustered clinical data, including population-averaged versus subject-specific effects, correlation structures, missing data, interpretation, R and SAS examples, and a worked clinical trial example.
Frailty Models for Clustered Survival Data
A practical guide to frailty models for clustered survival data, including shared frailty, gamma frailty, log-normal frailty, hazard interpretation, within-cluster dependence, estimation, model diagnostics, R implementation, and a clinical trial worked example.