Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects or behaviors.
Hypotheses:
Interpretation of Kendall's W
Kendall's W ranges from 0 to 1. A value of 1 indicates perfect agreement among the raters, meaning all raters assigned identical ranks to the items. A value of 0 suggests no agreement beyond what would be expected by chance. Intermediate values indicate varying degrees of concordance, with values closer to 1 indicating stronger agreement.
Ties in Ranking
In cases where ties occur among the ranks, adjustments are made to the calculation of Kendall's W. When ties are present, a correction factor is applied to account for the reduced variability in the rankings. This adjustment ensures that the measure remains accurate even when identical ranks are assigned to different items by the same rater.
Kendall's W provides a robust and straightforward way to assess the consensus among multiple evaluators, particularly when data is ordinal and ranks are involved.
Du chapitre 13:
Now Playing
Nonparametric Statistics
230 Vues
Nonparametric Statistics
658 Vues
Nonparametric Statistics
225 Vues
Nonparametric Statistics
667 Vues
Nonparametric Statistics
96 Vues
Nonparametric Statistics
69 Vues
Nonparametric Statistics
86 Vues
Nonparametric Statistics
84 Vues
Nonparametric Statistics
93 Vues
Nonparametric Statistics
147 Vues
Nonparametric Statistics
580 Vues
Nonparametric Statistics
654 Vues
Nonparametric Statistics
668 Vues
Nonparametric Statistics
585 Vues
Nonparametric Statistics
551 Vues
See More