COMPARE {EFAtools}

Compare two vectors or matrices (communalities or loadings)

Description

The function takes two objects of the same dimensions containing numeric information (loadings or communalities) and returns a list of class COMPARE containing summary information of the differences of the objects.

Usage

COMPARE(
  x,
  y,
  reorder = c("congruence", "names", "none"),
  corres = TRUE,
  thresh = 0.3,
  digits = 4,
  m_red = 0.001,
  range_red = 0.001,
  round_red = 3,
  print_diff = TRUE,
  na.rm = FALSE,
  x_labels = c("x", "y"),
  plot = TRUE,
  plot_red = 0.01
)

Arguments

x

matrix, or vector. Loadings or communalities of a factor analysis output.

y

matrix, or vector. Loadings or communalities of another factor analysis output to compare to x.

reorder

character. Whether and how elements / columns should be reordered. If "congruence" (default), reordering is done according to Tuckers correspondence coefficient, if "names", objects according to their names, if "none", no reordering is done.

corres

logical. Whether factor correspondences should be compared if a matrix is entered.

thresh

numeric. The threshold to classify a pattern coefficient as substantial. Default is .3.

digits

numeric. Number of decimals to print in the output. Default is 4.

m_red

numeric. Number above which the mean and median should be printed in red (i.e., if .001 is used, the mean will be in red if it is larger than .001, otherwise it will be displayed in green.) Default is .001.

range_red

numeric. Number above which the min and max should be printed in red (i.e., if .001 is used, min and max will be in red if the max is larger than .001, otherwise it will be displayed in green. Default is .001). Note that the color of min also depends on max, that is min will be displayed in the same color as max.

round_red

numeric. Number above which the max decimals to round to where all corresponding elements of x and y are still equal are displayed in red (i.e., if 3 is used, the number will be in red if it is smaller than 3, otherwise it will be displayed in green). Default is 3.

print_diff

logical. Whether the difference vector or matrix should be printed or not. Default is TRUE.

na.rm

logical. Whether NAs should be removed in the mean, median, min, and max functions. Default is FALSE.

x_labels

character. A vector of length two containing identifying labels for the two objects x and y that will be compared. These will be used as labels on the x-axis of the plot. Default is "x" and "y".

plot

logical. If TRUE (default), a plot illustrating the differences will be shown.

plot_red

numeric. Threshold above which to plot the absolute differences in red. Default is .001.

Value

A list of class COMPARE containing summary statistics on the differences of x and y.

diff

The vector or matrix containing the differences between x and y.

mean_abs_diff

The mean absolute difference between x and y.

median_abs_diff

The median absolute difference between x and y.

min_abs_diff

The minimum absolute difference between x and y.

max_abs_diff

The maximum absolute difference between x and y.

max_dec

The maximum number of decimals to which a comparison makes sense. For example, if x contains only values up to the third decimals, and y is a normal double, max_dec will be three.

are_equal

The maximal number of decimals to which all elements of x and y are equal.

diff_corres

The number of differing variable-to-factor correspondences between x and y, when only the highest loading is considered.

diff_corres_cross

The number of differing variable-to-factor correspondences between x and y when all loadings >= thresh are considered.

g

The root mean squared distance (RMSE) between x and y.

settings

List of the settings used.

Examples

# A type SPSS EFA to mimick the SPSS implementation
EFA_SPSS_6 <- EFA(test_models$case_11b$cormat, n_factors = 6, type = "SPSS")

# A type psych EFA to mimick the psych::fa() implementation
EFA_psych_6 <- EFA(test_models$case_11b$cormat, n_factors = 6, type = "psych")

# compare the two
COMPARE(EFA_SPSS_6$unrot_loadings, EFA_psych_6$unrot_loadings,
        x_labels = c("SPSS", "psych"))