plot_pc_input function

Plot Scores from Significant PCs Against PCA Input

It is sometimes useful to see the relationship between PCs and the raw values of the input data fed into PCA. This function takes the results of running pca_test, the scores for each speaker from the pca object, and the raw data fed into the PCA analysis. In the usual model-to-pca analysis pipeline, the resulting plot depicts by-speaker random intercepts for each vowel and an indication of which variables are significantly loaded onto the PCs. It allows the researcher to visualise the strength of the relationship between intercepts and PC scores.

plot_pc_input(pca_object, pca_data, pca_test)

Arguments

• pca_object: Output of prcomp.
• pca_data: Data fed into prcomp. This should not include speaker identifiers.
• pca_test: Output of pca_test

Returns

a ggplot object.

Examples

pca_data <- onze_intercepts |> dplyr::select(-speaker)
onze_pca <- prcomp(pca_data, scale = TRUE)
onze_pca_test <- pca_test(pca_data, n = 10)
plot_pc_input(onze_pca, pca_data, onze_pca_test)