correlation_map.fmri_model — correlation_map.fmri

Heatmap of pairwise correlations between the columns of an fmri_model's combined event + baseline design matrix, grouped into panels by model term (event terms, drift, nuisance).

By default (within_run = TRUE) each column is centred within each run and the run-intercept columns are dropped before correlating. This shows the collinearity that matters for estimation once run means are modelled, and removes spurious correlations that zero-padding creates between columns belonging to different runs. Cells for pairs of columns that live in different runs are left blank.

Usage

# S3 method for class 'fmri_model'
correlation_map(
  x,
  method = c("pearson", "spearman"),
  half_matrix = TRUE,
  absolute_limits = TRUE,
  within_run = TRUE,
  label_values = NULL,
  ...
)

Arguments

x: An fmri_model.
method: Correlation method (e.g., "pearson", "spearman").
half_matrix: Logical; if TRUE (default), display only the lower triangle.
absolute_limits: Logical; if TRUE, the colour scale spans -1 to 1; otherwise it spans plus or minus the largest absolute correlation shown.
within_run: Logical; centre columns within runs and drop run intercepts before correlating (default TRUE). FALSE correlates the raw columns.
label_values: Logical or NULL; print correlations in the cells. NULL (default) labels every cell when there are at most 12 columns, and otherwise only cells with |r| >= 0.3 that involve an event regressor.
...: Additional arguments passed to geom_tile.

Value

A ggplot2 object.