The problem of whether the rankings of some objects given by a set of judges show any agreement or are more or less independent is addressed. The most familiar measure for concordance is the Kendall W coefficient. Classical tests for concordance are the Friedman and tests. Legendre (2005) showed via simulation that the Friedman test is too conservative and less powerful than its permutation version but his study was very limited. In this paper, the study of Legendre is deeply extended. It is shown that the Friedman test is too conservative and less powerful than both the F test and the permutation test for concordance which always have a correct size and very similar power. The F test should be preferred because it is computationally much...
<p>Results of a Friedman test to compare prediction methods across different datasets and feature se...
The Friedman test is often used for a randomized complete block design when the normality assumption...
A fundamental task in machine learning is to compare the performance of multiple algorithms. This is...
The problem of whether the rankings of some objects given by a set of judges show any agreement or a...
The problem of whether the rankings of some objects given by a set of criteria (or judges) show any ...
In several research areas such as psychology, social science, and medicine, studies are conducted in...
Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement ...
Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement ...
A number of nonparametric tests are compared empirically for a randomized block layout. We assess te...
International audienceThis communication explores the benefit of one data analysis method implicativ...
The Friedman test is used to nonparametrically test the null hypothesis of equality of the treatment...
This communication explores the benefit of one data analysis method implicativeanalysis such as Gras...
A novel presentation of rank and permutation tests, with accessible guidance to applications in R. N...
When the null hypothesis of Friedman's test is rejected, there is a wide variety of multiple compari...
<p>Results of a Friedman test to compare prediction methods across different datasets and feature se...
The Friedman test is often used for a randomized complete block design when the normality assumption...
A fundamental task in machine learning is to compare the performance of multiple algorithms. This is...
The problem of whether the rankings of some objects given by a set of judges show any agreement or a...
The problem of whether the rankings of some objects given by a set of criteria (or judges) show any ...
In several research areas such as psychology, social science, and medicine, studies are conducted in...
Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement ...
Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement ...
A number of nonparametric tests are compared empirically for a randomized block layout. We assess te...
International audienceThis communication explores the benefit of one data analysis method implicativ...
The Friedman test is used to nonparametrically test the null hypothesis of equality of the treatment...
This communication explores the benefit of one data analysis method implicativeanalysis such as Gras...
A novel presentation of rank and permutation tests, with accessible guidance to applications in R. N...
When the null hypothesis of Friedman's test is rejected, there is a wide variety of multiple compari...
<p>Results of a Friedman test to compare prediction methods across different datasets and feature se...
The Friedman test is often used for a randomized complete block design when the normality assumption...
A fundamental task in machine learning is to compare the performance of multiple algorithms. This is...