david-b3/statistics_multiple-mean-comparison_anova_and_non-parametric-tests

Perform a STEP by STEP multiple mean comparison analysis on R

Perform a STEP by STEP multiple mean comparison analysis on R

This code has been developed to realize the complete process of a multiple mean comparison (ANOVA and non-parametric tests) on R.

It is composed of:

1. Importation on the datafile
2. Descriptive Statistics (Mean, Standard Deviation)
3. Visualization of the data, detection of outliers
4. Normality and homogeneity assumption
5. Parametric and non-parametric test for multiple means comparison
6. Corresponding Post-Hoc tests
7. Visualization of the data (graph) with significance bars and stars
8. Exportation of the results

STUDY-CASE: 22 subjects played a football game. Before the match ("PreMatch"), 24h, 48h and 72h after, they performed force measurements (IMVC : isometric maximal voluntary contraction). After the match, subjects were divided in 2 groups experiencing 25-min sessions of either cold water immersion (CWI, n = 11) or hot water immersion (HWI, n = 11). We want to know if the immersion temperature have an impact on the force recovery. To do so, we will perform a Multiple Mean Comparison analysis.

Note: all data in Example-MultipleMeanComparison.CSV have been randomly created. They are plausible values for IMVC (Isometric Maximal Voluntary Contraction) but invented for the example.