Coordinates of the Individuals on the Axes of an Analysis

The coordinates of each individual on the axes of a principal component analysis or of a multiple correspondence analysis, to write into the data frame with dplyr::mutate(), like hierarchical_clust:

`data <- data |> mutate(axe1 = axis_coord(res, 1))`

An analysis made with multiple_correspondence_analysis is computed on the distinct answer profiles, so its `$ind$coord` has one row per profile: `axis_coord()` gives each individual the coordinate of its profile. In a correspondence analysis, each individual takes the coordinate of its level.

Usage

axis_coord(res, axes = 1, margin = "rows")

Arguments

res: An analysis made with multiple_correspondence_analysis, principal_component_analysis or correspondence_analysis (or with FactoMineR::MCA(), PCA() or CA(), or GDAtools::speMCA() or csMCA()).
axes: The axes. Several axes give a data frame, which mutate() writes as several columns, named after `axes` when it has names (`c(axe1 = 1, axe2 = 2)`), else `axis1`, `axis2`...
margin: For a correspondence analysis, the variable whose levels give the coordinates: `"rows"`, the default, or `"columns"`.

Value

One value per row of the data frame: inside dplyr::mutate(), of the data frame being written, with `NA` on the rows the analysis did not use (when it was made on a subset of the population); outside, of the data frame the analysis started from. For a correspondence analysis outside mutate(), one value per level, named after it.

Examples

data(tea, package = "FactoMineR")
res.mca <- multiple_correspondence_analysis(tea, 1:18)

tea <- tea |>
  dplyr::mutate(axe1 = axis_coord(res.mca, 1),
                axis_coord(res.mca, c(axe2 = 2, axe3 = 3)))

# How much of the first axis does age explain?
summary(stats::lm(axe1 ~ age_Q, data = tea))$r.squared
#> [1] 0.008006629