Confidence Intervals Explained for Clinical Trials
A practical guide to confidence intervals in clinical trials, including interpretation, treatment effects, standard errors, precision, hazard ratios, risk differences, odds ratios, non-inferiority, equivalence, subgroup analyses, and reporting.
Closed Testing Procedures Explained
A practical guide to closed testing procedures for multiplicity control in clinical trials, including the closure principle, elementary hypotheses, local tests, adjusted p-values, gatekeeping, strong family-wise error control, and a complete worked example.
Checking Regression Assumptions and Diagnostics
A practical guide to checking regression assumptions and diagnostics in clinical research, including linearity, normality, homoscedasticity, independence, influential observations, multicollinearity, residual diagnostics, transformations, and R and SAS examples.
Certifications Worth Pursuing in Biostatistics
A practical guide to certifications and professional credentials worth pursuing in biostatistics, including ASA accreditation, SAS certifications, analytics credentials, clinical research certifications, and when certifications are not worth the investment.
Central Limit Theorem for Clinical Researchers
A practical guide to the Central Limit Theorem for clinical researchers, including sampling distributions, standard errors, normal approximations, confidence intervals, hypothesis tests, and clinical trial applications.
Bootstrapping and Resampling Methods in Clinical Trials
A practical guide to bootstrapping and resampling methods in clinical trials, including nonparametric bootstrap confidence intervals, treatment effects, bias correction, BCa intervals, clustered data, survival outcomes, missing data, permutation tests, and R examples.
Bonferroni Correction Explained
A practical guide to the Bonferroni correction for multiple comparisons, including family-wise error rate, adjusted significance levels, adjusted p-values, clinical trial examples, confidence intervals, R implementation, and common mistakes.
Analyzing Change from Baseline in Clinical Trials
A practical guide to analyzing change from baseline in clinical trials, including change scores, ANCOVA, repeated-measures models, MMRM, least-squares means, percent change, baseline adjustment, missing data, interpretation, and worked examples.
Analysis of Longitudinal Binary Outcomes
A practical guide to analyzing longitudinal binary outcomes in clinical research using GEE and generalized linear mixed models, including marginal versus subject-specific effects, working correlation structures, missing data, interpretation, R and SAS examples, and a complete worked example.
Accelerated Failure Time Models Explained
A practical guide to accelerated failure time models for clinical survival analysis, including the AFT interpretation, survival-time ratios, Weibull and log-normal models, censoring, model fitting in R, interpretation, diagnostics, and a complete worked example.