“…This occurs in longitudinal time-dependent assessments (for example, before and after measures, clinical trials, studies of the progress over time of intervention), 1,2 when measures of different areas of the same subject are assessed (for example, comparisons between adjacent structures: healthy vs. sick and split body interventions), 3,4 or when measures are obtained from the same organism challenged by different stimuli (for example, response to drugs, temperature, or pain). 5,6 Variables for which there is a link (whether temporal or organic) between different measures generate data that should be analyzed in a dependent manner (paired or correlated), which minimizes the variability between these measures, maximizing the analytical power, and requiring smaller sample sizes for statistical inferences. However, quantitative analysis of dependent data is sensitive to different analytical assumptions, which demands caution when choosing which statistical techniques to employ and when interpreting their results.…”