ABSTRACT
This chapter presents statistical methods for comparing treatment groups in clinical trials using the R and SAS systems. It also presents two datasets from clinical trials with the first dataset for continuous outcome and the second for categorical outcome. The chapter analyses this dataset to test whether treatment A (new drug) may be effective in lowering diastolic blood pressure (DBP) as compared to B (placebo) and describes changes in DBP across the times at which it was measured. It introduces the associated statistical models for these types of data which include the t-test, the one-way and two-way analysis of variances (ANOVA) for univariate outcome and multivariate analysis of variance (MANOVA) for the multiple changes from baseline to the four post-baseline measurements to incorporate the correlations among these four multiple outcomes. The chapter also introduces Pearson's chisquare test to draw comparisons with other methods of analyses of the clinical trial on duodenal ulcer healing.
