Usage: [RANKS, RESPONSE, TREATMENT, BLOCKS] = tiedrank2 (X, REPS, DIM)
The entire data matrix X is ranked from smallest to largest, where average ranks are assigned in the case of ties and NaN values are ignored. This is what Conover referred to as the RT-1 type procedure .
If there is more than one observation per row-column "cell", use the scalar argument REPS to indicate the (largest) number of observations per cell. Each cell corresponds to REPS consecutive rows in one column of X if DIM equals 1 (default), or REPS consecutive columns in one row of X if DIM equals 2.
The output from tiedrank2 can be used as input for the ANOVA functions as a more powerful alternative to using bespoke nonparametric tests .
Please see function help for example usage in a wide variety of tests.
 Conover, W. J., & Iman, R. L. (1981).
Rank transformations as a bridge between parametric and nonparametric statistics.
American Statistician, 35, 124-129.
 Zimmerman, D. W., & Zumbo, Bruno, D. (1993).
Relative power of the Wilcoxon test, the Friedman test, and repeated-measures ANOVA on ranks.
Journal of Experimental Education, 62, 75-86.
 Conover, W. J., & Iman, R. L. (1982).
Analysis of Covariance using the Rank Transformations.
Biometrics, 38, 715-724.
Andrew Penn (2022). tiedrank2 (https://www.mathworks.com/matlabcentral/fileexchange/72399-tiedrank2), MATLAB Central File Exchange. Retrieved .
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