One-Sample and Two-Sample t-Tests in Clinical Data
A practical guide to one-sample and two-sample t-tests in clinical research, including hypotheses, assumptions, pooled and Welch t-tests, paired analyses, confidence intervals, effect sizes, clinical interpretation, and implementation in R and SAS.
Non-Parametric Tests: Wilcoxon and Mann-Whitney U
A practical guide to non-parametric testing in clinical research, including the Wilcoxon signed-rank test, Wilcoxon rank-sum test, Mann-Whitney U test, assumptions, hypotheses, exact and asymptotic methods, effect sizes, clinical examples, and R implementation.
Introduction to Statistical Power
A practical introduction to statistical power in clinical research, including type II error, effect size, sample size, significance level, power calculations, interpretation, and common mistakes.
Fisher’s Exact Test for Small Sample Sizes
A practical guide to Fisher
Effect Size Measures in Clinical Research
A practical guide to effect size measures in clinical research, including risk difference, relative risk, odds ratio, hazard ratio, mean differences, standardized mean differences, number needed to treat, and interpretation in clinical trials.
Descriptive Statistics for Clinical Trial Data
A practical guide to descriptive statistics for clinical trial data, including means, medians, standard deviations, quartiles, confidence intervals, categorical summaries, baseline characteristics, laboratory data, adverse events, missing data, outliers, and clinical trial reporting in SAS and R.
Correlation vs. Causation in Clinical Research
A practical guide to correlation vs. causation in clinical research, including confounding, selection bias, reverse causation, randomized trials, causal diagrams, observational studies, regression adjustment, mediation, and practical examples.
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.
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.