Visualization of a correlation matrix

ggcorrmat(
data,
cor.vars = NULL,
cor.vars.names = NULL,
output = "plot",
matrix.type = "full",
matrix.method = "square",
type = "parametric",
beta = 0.1,
k = 2L,
sig.level = 0.05,
conf.level = 0.95,
bf.prior = 0.707,
pch = "cross",
ggcorrplot.args = list(outline.color = "black"),
package = "RColorBrewer",
palette = "Dark2",
colors = c("#E69F00", "white", "#009E73"),
ggtheme = ggplot2::theme_bw(),
ggstatsplot.layer = TRUE,
ggplot.component = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
messages = TRUE,
...
)

## Arguments

data Dataframe from which variables specified are preferentially to be taken. List of variables for which the correlation matrix is to be computed and visualized. If NULL (default), all numeric variables from data will be used. Optional list of names to be used for cor.vars. The names should be entered in the same order. Character that decides expected output from this function. If "plot", the visualization matrix will be returned. If "dataframe" (or literally anything other than "plot"), a dataframe containing all details from statistical analyses (e.g., correlation coefficients, statistic values, p-values, no. of observations, etc.) will be returned. Character, "full" (default), "upper" or "lower", display full matrix, lower triangular or upper triangular matrix. The visualization method of correlation matrix to be used. Allowed values are "square" (default) or "circle". Type of association between paired samples required (""parametric": Pearson's product moment correlation coefficient" or ""nonparametric": Spearman's rho" or ""robust": percentage bend correlation coefficient" or ""bayes": Bayes Factor for Pearson's r"). Corresponding abbreviations are also accepted: "p" (for parametric/pearson), "np" (nonparametric/spearman), "r" (robust), "bf" (for bayes factor), resp. bending constant (Default: 0.1). For more, see WRS2::pbcor(). Number of digits after decimal point (should be an integer) (Default: k = 2L). Significance level (Default: 0.05). If the p-value in p-value matrix is bigger than sig.level, then the corresponding correlation coefficient is regarded as insignificant and flagged as such in the plot. Relevant only when output = "plot". Scalar between 0 and 1. If unspecified, the defaults return 95% lower and upper confidence intervals (0.95). A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors. What adjustment for multiple tests should be used? ("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"). See stats::p.adjust for details about why to use "holm" rather than "bonferroni"). Default is "none". If adjusted p-values are displayed in the visualization of correlation matrix, the adjusted p-values will be used for the upper triangle, while unadjusted p-values will be used for the lower triangle of the matrix. Decides the point shape to be used for insignificant correlation coefficients (only valid when insig = "pch"). Default: pch = "cross". A list of additional (mostly aesthetic) arguments that will be passed to ggcorrplot::ggcorrplot function. The list should avoid any of the following arguments since they are already internally being used by ggstatsplot: corr, method, p.mat, sig.level, ggtheme, colors, matrix.type, lab, pch, legend.title, digits. Name of the package from which the given palette is to be extracted. The available palettes and packages can be checked by running View(paletteer::palettes_d_names). Name of the package from which the given palette is to be extracted. The available palettes and packages can be checked by running View(paletteer::palettes_d_names). A vector of 3 colors for low, mid, and high correlation values. If set to NULL, manual specification of colors will be turned off and 3 colors from the specified palette from package will be selected. A function, ggplot2 theme name. Default value is ggplot2::theme_bw(). Any of the ggplot2 themes, or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). Logical that decides whether theme_ggstatsplot theme elements are to be displayed along with the selected ggtheme (Default: TRUE). theme_ggstatsplot is an opinionated theme layer that override some aspects of the selected ggtheme. A ggplot component to be added to the plot prepared by ggstatsplot. This argument is primarily helpful for grouped_ variant of the current function. Default is NULL. The argument should be entered as a function. The text for the plot title. The text for the plot subtitle. Will work only if results.subtitle = FALSE. The text for the plot caption. Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE). Currently ignored.

## Value

Correlation matrix plot or a dataframe containing results from pairwise correlation tests. The package internally uses ggcorrplot::ggcorrplot for creating the visualization matrix, while the correlation analysis is carried out using the correlation::correlation function.

## References

https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggcorrmat.html

grouped_ggcorrmat ggscatterstats grouped_ggscatterstats

## Examples

# \donttest{
# for reproducibility
set.seed(123)

# if cor.vars not specified, all numeric variables used
ggstatsplot::ggcorrmat(iris)

# to get the correlalogram
# note that the function will run even if the vector with variable names is
# not of same length as the number of variables
ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
type = "robust",
cor.vars = sleep_total:bodywt,
cor.vars.names = c("total sleep", "REM sleep"),
matrix.type = "lower"
)
#> Warning: No. of variable names doesn't equal no. of variables.#>
# to get the correlation analyses results in a dataframe
ggstatsplot::ggcorrmat(
data = ggplot2::msleep,
cor.vars = sleep_total:bodywt,
output = "dataframe"
)
#> # A tibble: 15 x 10
#>    parameter1  parameter2       r  ci_low ci_high        t    df         p method   nobs
#>    <chr>       <chr>        <dbl>   <dbl>   <dbl>    <dbl> <int>     <dbl> <chr>   <int>
#>  1 sleep_total sleep_rem    0.752  0.617   0.844      8.76    59 2.92e- 12 Pearson    61
#>  2 sleep_total sleep_cycle -0.474 -0.706  -0.150     -2.95    30 6.17e-  3 Pearson    32
#>  3 sleep_total awake       -1.00  -1.00   -1.00   -5329.      81 2.42e-226 Pearson    83
#>  4 sleep_total brainwt     -0.360 -0.569  -0.108     -2.84    54 6.35e-  3 Pearson    56
#>  5 sleep_total bodywt      -0.312 -0.494  -0.103     -2.96    81 4.09e-  3 Pearson    83
#>  6 sleep_rem   sleep_cycle -0.338 -0.614   0.0120    -1.97    30 5.84e-  2 Pearson    32
#>  7 sleep_rem   awake       -0.752 -0.844  -0.617     -8.76    59 2.91e- 12 Pearson    61
#>  8 sleep_rem   brainwt     -0.221 -0.476   0.0670    -1.54    46 1.31e-  1 Pearson    48
#>  9 sleep_rem   bodywt      -0.328 -0.535  -0.0826    -2.66    59 9.95e-  3 Pearson    61
#> 10 sleep_cycle awake        0.474  0.150   0.706      2.95    30 6.17e-  3 Pearson    32
#> 11 sleep_cycle brainwt      0.852  0.709   0.927      8.60    28 2.42e-  9 Pearson    30
#> 12 sleep_cycle bodywt       0.418  0.0809  0.669      2.52    30 1.73e-  2 Pearson    32
#> 13 awake       brainwt      0.360  0.108   0.569      2.84    54 6.35e-  3 Pearson    56
#> 14 awake       bodywt       0.312  0.103   0.494      2.96    81 4.09e-  3 Pearson    83
#> 15 brainwt     bodywt       0.934  0.889   0.961     19.2     54 9.16e- 26 Pearson    56# }