Introduction.- Reading and transforming data.- Statistics for comparing means and proportions.- R graphics and trellis plots.- Analysis of variance: repeated-measures.- Linear and logistic regression.- Statistical power and sample size considerations.- Item Response Theory (IRT) and psychometric methods.- Imputation of missing data.- Linear mixed-effects models in repeated-measures.- Linear mixed-effects models in cluster-randomized studies.