Negative Binomial Regression for Overdispersed Count Data
A practical clinical biostatistics tutorial on negative binomial regression for overdispersed count data, including the model, dispersion parameter, incidence rate ratios, offsets, worked clinical examples, SAS and R code, model checking, interpretation, and common mistakes.
Multiple Imputation: A Practical Guide
A practical guide to multiple imputation for missing data, covering MCAR, MAR, and MNAR assumptions, the imputation-analysis-pooling framework, MICE, predictive mean matching, Rubin
Multiple Imputation in R: A Step-by-Step Guide
A practical step-by-step guide to multiple imputation in R using mice, including missing-data assumptions, imputation models, chained equations, diagnostics, pooling, regression analysis, sensitivity analysis, and clinical-trial examples.
Multiple Comparison Procedures for Dose-Ranging Studies
A practical guide to multiple comparison procedures for dose-ranging clinical trials, including Dunnett
Multinomial Logistic Regression Explained
A practical guide to multinomial logistic regression for clinical research, including baseline-category logits, interpretation of coefficients and odds ratios, global tests, predicted probabilities, a worked clinical example, R and SAS implementation, model diagnostics, and common mistakes.
Model Selection: AIC vs. BIC in Clinical Research
A practical guide to AIC and BIC for selecting statistical models in clinical research, including the formulas, interpretation, worked examples, likelihood-based model comparison, nested and non-nested models, regression, survival analysis, mixed models, and practical guidance for clinical statisticians.
Milestone Survival Analysis in Oncology Trials
A practical guide to milestone survival analysis in oncology trials, including fixed-time overall survival and progression-free survival probabilities, Kaplan-Meier estimation, confidence intervals, treatment comparisons, censoring, estimands, and R and SAS implementation.
MMRM Part 2: Sensitivity Analyses and Robustness
A practical guide to sensitivity analyses and robustness checks for mixed models for repeated measures (MMRM), including covariance structures, missing-data assumptions, multiple imputation, pattern-mixture models, reference-based imputation, tipping-point analyses, alternative estimands, and SAS and R implementation.
Logistic Regression Part 2: A Worked Clinical Example
A practical worked clinical example of multivariable logistic regression, including model specification, odds ratios, confidence intervals, adjusted treatment effects, predicted probabilities, interpretation, R implementation, SAS implementation, model diagnostics, and common reporting mistakes.
Log-Rank Test for Comparing Survival Curves
A practical guide to the log-rank test for comparing survival curves, including hypotheses, observed versus expected events, the test statistic, worked clinical example, interpretation, assumptions, stratified log-rank tests, and common mistakes.