CAinterprTools (version 1.1.0)

rows.corr: Chart of rows correlation with a selected dimension

Description

This function allows to calculate the correlation (sqrt(COS2)) of the row categories with the selected dimension.

Usage

rows.corr(
  data,
  x = 1,
  categ.sort = TRUE,
  filter = FALSE,
  leg = TRUE,
  dotprightm = 5,
  cex.leg = 0.6,
  cex.labls = 0.75,
  leg.x.spc = 1,
  leg.y.spc = 1
)

Arguments

data

Name of the dataset (must be in dataframe format).

x

Dimension for which the row categories correlation is returned (1st dimension by default).

categ.sort

Logical value (TRUE/FALSE) which allows to sort the categories in descending order of correlation with the selected dimension. TRUE is set by default.

filter

Filter the column categories listed in the top-right legend, only showing those who have a major contribution to the definition of the selected dimension.

leg

Enable (TRUE; default) or disable (FALSE) the legend at the right-hand side of the dot plot.

dotprightm

Increases the empty space between the right margin of the dot plot and the left margin of the legend box.

cex.leg

Adjust the size of the legend's characters.

cex.labls

Adjust the size of the dot plot's labels.

leg.x.spc

Adjust the horizontal space of the chart's legend. See more info from the 'legend' function's help (?legend).

leg.y.spc

Adjust the y interspace of the chart's legend. See more info from the 'legend' function's help (?legend).

Details

The function displays the correlation of the row categories with the selected dimension; the parameter categ.sort=TRUE arrange the categories in decreasing order of correlation. At the left-hand side, the categories' labels show a symbol (+ or -) according to which side of the selected dimension they are correlated, either positive or negative. The categories are grouped into two groups: categories correlated with the positive ('pole +') or negative ('pole -') pole of the selected dimension. At the right-hand side, a legend (which is enabled/disabled using the 'leg' parameter) indicates the column categories' contribution (in permills) to the selected dimension (value enclosed within round brackets), and a symbol (+ or -) indicating whether they are actually contributing to the definition of the positive or negative side of the dimension, respectively. Further, an asterisk (*) flags the categories which can be considered major contributors to the definition of the dimension.

See Also

rows.corr.scatter , cols.corr , cols.corr.scatter

Examples

# NOT RUN {
data(greenacre_data)

#Plots the correlation of the row categories with the 1st CA dimension.
rows.corr(greenacre_data, 1, categ.sort=TRUE)

# }