Compute correlation between test indexes — correlate

Given raw data, computes selected type of pairwise correlations ("Pearson" by default) of all selected indexes and plots them. Optionally, the user can specify an "ideal" correlation matrix of the same variables for comparison purposes.

Usage

correlate_indexes(
  d0,
  v = setNames(c("moca_7", "mmse_7", "moca_cloc", "cloc", "vf_s", "vf_k", "moca_5words",
    "mmse_3words", "moca_cube", "mmse_pent", "moca_abs", "moca_anim"), c("MoCA Sevens",
    "MMSE Sevens", "MoCA Clock", "Clock Drawing", "VF S", "VF K", "MoCA 5 words",
    "MMSE 3 words", "MoCA Cube", "MMSE Pent.", "MoCA Abs.", "MoCA An.")),
  ideal = NULL,
  ...
)

Arguments

d0: Input data.
v: Named character vector of variables to be included.
ideal: Optionally a matrix of ideal values. Write NULL for the default or NA if no ideal matrix should be plotted.
...: Other variables for cor()

Value

A list containing:

R_observed: Correlation matrix of observed data
R_ideal: Correlation matrix of the "ideal" pattern