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# Rank Correlation

KNIME Statistic Nodes version 4.2.1.v202008251159 by KNIME AG, Zurich, Switzerland

Calculates for each pair of selected columns a correlation coefficient, i.e. a measure of the correlation of the two variables.

All measures are based on the rank of the cells. Where the rank of a cell value refers to its position in a sorted list of all entries. All correlation can be calculated on any kind of DataColumn. However please note that we use the default ordering of the values. If there is no ordering defined in the column, a string representation will be used. The node uses fractional ranks for equal values. Spearman's rank correlation coefficient is a statistical measure of the strength of a monotonic relationship between paired data. Where the monotonic relationship is characterised by a relationship between ordered sets that preserves the given order, i.e., either never increases or never decreases as its independent variable increases. The value of this measure ranges from -1 (strong negative correlation) to 1 (strong positive correlation). A perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. For Spearman's rank correlation coefficient the p-value and degrees of freedom are computed. The p-value indicates the probability of an uncorrelated system producing a correlation at least as extreme, if the mean of the correlation is zero and it follows a t-distribution with df degrees of freedom.
Goodman and Kruskal's gamma as well as Kendall's tau rank correlation coefficient is used to measure the strength of association between two measured quantities. Both are based on the number of concordant and discordant pairs. Kendall's Tau A and Tau B coefficients can be considered as standardized forms of Gamma. The difference between Tau A and Tau B is that Tau A statistic does not consider tied values, while Tau B makes adjustments for them. By tied observations we consider two or more observations having the same value. Both Kruskal's gamma and Kendall's Tau A are mostly suitable for square tables, whereas Tau B is most appropriately used for rectangular tables. The coefficients must be in the range from −1 (100% negative association, or perfect inversion) to +1 (100% positive association, or perfect agreement). A value of zero indicates the absence of association.

Rows containing Missing Values will be ignored, not used for the calculations. For other behaviors please resolve them before.

## Options

Correlation Type
Chose the type of correlation here. There are the Spearman Correlation, two types of Kendalls Tau and Goodman and Kruskal's Gamma.

#### Manual Selection

Include
This list contains the names of those columns in the input table for which correlation values should be computed.
Exclude
This list contains the names of those columns in the input table to be left out of the computation.
Filter
Use one of these fields to filter either the Include or Exclude list for certain column names or name substrings.
Buttons
Use these buttons to move columns between the Include and Exclude list. Single-arrow buttons will move all selected columns. Double-arrow buttons will move all columns (filtering is taken into account).
Enforce Exclusion
Select this option to enforce the current exclusion list to stay the same even if the input table specification changes. If some of the excluded columns are not available anymore, a warning is displayed. (New columns will automatically be added to the inclusion list.)
Enforce Inclusion
Select this option to enforce the current inclusion list to stay the same even if the input table specification changes. If some of the included columns are not available anymore, a warning is displayed. (New columns will automatically be added to the exclusion list.)

#### Wildcard/Regex Selection

Type a search pattern which matches columns to move into the Include list. You can use either Wildcards ('?' matching any character, '*' matching a sequence of any characters) or Regex. You can specify whether your pattern should be case sensitive.

#### Type Selection

Select the column types that you want to include. Column types that are currently not present are depicted in italic.
Include only column pairs with a valid correlation
Check this option if only the column pairs where the correlation could be computed should be included in the output table. Column pairs where the correlation could not be computed are then omitted from the output table.
p-value
Select which p-value should be computed for Spearman's rank correlation coefficient.
• "two-sided" corresponds to the probability of obtaining a correlation value that is at least as extreme as the observed correlation.
• "one-sided (right)" corresponds to the probability of obtaining a correlation value that shows even greater positive association.
• "one-sided (left)" corresponds to the probability of obtaining a correlation value that shows even greater negative association.

## Input Ports Numeric input data to evaluate

## Output Ports Correlation variables, p-values and degrees of freedom. Correlation variables in a matrix representation. A model containing the correlation measures. This model is appropriate to be read by the Correlation Filter node. A table containing the fractional ranks of the columns. Where the rank corresponds to the values position in a sorted table.

## Views

Correlation Matrix
Squared table view showing the pair-wise correlation values of all columns. The color range varies from dark red (strong negative correlation), over white (no correlation) to dark blue (strong positive correlation). If a correlation value for a pair of column is not available, the corresponding cell contains a missing value (shown as cross in the color view).

## Installation

To use this node in KNIME, install KNIME Statistics Nodes from the following update site: