parallel_analysis {kim} | R Documentation |
Parallel analysis
Description
Conducts a parallel analysis to determine how many factors to retain in a factor analysis.
Usage
parallel_analysis(
data = NULL,
names_of_vars = NULL,
iterations = NULL,
percentile_for_eigenvalue = 95,
line_types = c("dashed", "solid"),
colors = c("red", "blue"),
eigenvalue_random_label_x_pos = NULL,
eigenvalue_random_label_y_pos = NULL,
unadj_eigenvalue_label_x_pos = NULL,
unadj_eigenvalue_label_y_pos = NULL,
label_offset_percent = 2,
label_size = 6,
dot_size = 5,
line_thickness = 1.5,
y_axis_title_vjust = 0.8,
title_text_size = 26,
axis_text_size = 22
)
Arguments
data |
a data object (a data frame or a data.table) |
names_of_vars |
names of the variables |
iterations |
number of random data sets. If no input is entered, this value will be set as 30 * number of variables. |
percentile_for_eigenvalue |
percentile used in estimating bias (default = 95). |
line_types |
types of the lines connecting eigenvalues.
By default, |
colors |
size of the dots denoting eigenvalues (default = 5). |
eigenvalue_random_label_x_pos |
(optional) x coordinate of the label for eigenvalues from randomly generated data. |
eigenvalue_random_label_y_pos |
(optional) y coordinate of the label for eigenvalues from randomly generated data. |
unadj_eigenvalue_label_x_pos |
(optional) x coordinate of the label for unadjusted eigenvalues |
unadj_eigenvalue_label_y_pos |
(optional) y coordinate of the label for unadjusted eigenvalues |
label_offset_percent |
How much should labels for the eigenvalue curves be offset, as a percentage of the plot's x and y range? (default = 2) |
label_size |
size of the labels for the eigenvalue curves (default = 6). |
dot_size |
size of the dots denoting eigenvalues (default = 5). |
line_thickness |
thickness of the eigenvalue curves (default = 1.5). |
y_axis_title_vjust |
position of the y axis title as a proportion of the range (default = 0.8). |
title_text_size |
size of the plot title (default = 26). |
axis_text_size |
size of the text on the axes (default = 22). |
Details
The following package(s) must be installed prior to running the function: Package 'paran' v1.5.2 (or possibly a higher version) by Alexis Dinno (2018), https://cran.r-project.org/package=paran
Examples
parallel_analysis(
data = mtcars, names_of_vars = c("disp", "hp", "drat"))
# parallel_analysis(
# data = mtcars, names_of_vars = c("carb", "vs", "gear", "am"))