ggcorrmat

From ggstatsplot v0.1.4 by Indrajeet Patil

Visualization of a correlation matrix

Usage

ggcorrmat(
  data,
  cor.vars = NULL,
  cor.vars.names = NULL,
  output = "plot",
  matrix.type = "full",
  method = "square",
  corr.method = "pearson",
  type = NULL,
  exact = FALSE,
  continuity = TRUE,
  beta = 0.1,
  digits = 2,
  k = NULL,
  sig.level = 0.05,
  conf.level = 0.95,
  p.adjust.method = "none",
  hc.order = FALSE,
  hc.method = "complete",
  lab = TRUE,
  package = "RColorBrewer",
  palette = "Dark2",
  direction = 1,
  colors = c("#E69F00", "white", "#009E73"),
  outline.color = "black",
  ggtheme = ggplot2::theme_bw(),
  ggstatsplot.layer = TRUE,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  caption.default = TRUE,
  lab.col = "black",
  lab.size = 5,
  insig = "pch",
  pch = 4,
  pch.col = "black",
  pch.cex = 11,
  tl.cex = 12,
  tl.col = "black",
  tl.srt = 45,
  messages = TRUE,
  return = NULL
)

Arguments

data: Dataframe from which variables specified are preferentially to be taken.
cor.vars: 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.
cor.vars.names: Optional list of names to be used for cor.vars. The names should be entered in the same order.
output, return: Character that decides expected output from this function: "plot" (for visualization matrix) or "correlations" (or "corr" or "r"; for correlation matrix) or "p-values" (or "p.values" or "p"; for a matrix of p-values) or "ci" (for a tibble with confidence intervals for unique correlation pairs; not available for robust correlation) or "n" (or "sample.size" for a tibble with sample sizes for each correlation pair).
matrix.type: Character, "full" (default), "upper" or "lower", display full matrix, lower triangular or upper triangular matrix.
method: Character argument that decides the visualization method of correlation matrix to be used. Allowed values are "square" (default), "circle"
corr.method, type: A character string indicating which correlation coefficient is to be computed ("pearson" (default) or "kendall" or "spearman"). "robust" can also be entered but only if output argument is set to either "correlations" or "p-values". The robust correlation used is percentage bend correlation (see ?WRS2::pball). Abbreviations will also work: "p" (for parametric/Pearson's r), "np" (nonparametric/Spearman's rho), "r" (robust).
exact: A logical indicating whether an exact p-value should be computed. Used for Spearman's rho. For more details, see ?stats::cor.test.
continuity: A logical. If TRUE, a continuity correction is used for Spearman's rho when not computed exactly (Default: TRUE).
beta: A numeric bending constant for percentage bend robust correlation coefficient (Default: 0.1).
digits, k: Decides the number of decimal digits to be displayed (Default: 2).
sig.level: 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. This argument is relevant only when output = "plot".
conf.level: Scalar between 0 and 1. If unspecified, the defaults return 95% lower and upper confidence intervals (0.95).
p.adjust.method: 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.
hc.order: Logical value. If TRUE, correlation matrix will be hc.ordered using hclust function (Default is FALSE).
hc.method: The agglomeration method to be used in hclust (see ?hclust).
lab: Logical value. If TRUE, correlation coefficient values will be displayed in the plot.
package: Name of package from which the palette is desired as string or symbol.
palette: Name of palette as string or symbol.
direction: Either 1 or -1. If -1 the palette will be reversed.
colors: 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.
outline.color: The outline color of square or circle. Default value is "gray".
ggtheme: 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.).
ggstatsplot.layer: 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.
title: The text for the plot title.
subtitle: The text for the plot subtitle.
caption: The text for the plot caption. If NULL, a default caption will be shown.
caption.default: Logical that decides whether the default caption should be shown (default: TRUE).
lab.col: Color to be used for the correlation coefficient labels (applicable only when lab = TRUE).
lab.size: Size to be used for the correlation coefficient labels (applicable only when lab = TRUE).
insig: Character used to show specialized insignificant correlation coefficients ("pch" (default) or "blank"). If "blank", the corresponding glyphs will be removed; if "pch" is used, characters (see ?pch for details) will be added on the corresponding glyphs.
pch: Decides the glyphs (read point shapes) to be used for insignificant correlation coefficients (only valid when insig = "pch"). Default value is pch = 4.
pch.col, pch.cex: The color and the cex (size) of pch (only valid when insig = "pch"). Defaults are pch.col = "#F0E442" and pch.cex = 10.
tl.cex, tl.col, tl.srt: The size, the color, and the string rotation of text label (variable names, i.e.).
messages: Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE).

Value

Correlation matrix plot or correlation coefficient matrix or matrix of p-values.

References

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

Examples

# NOT RUN {
# for reproducibility
set.seed(123)

# if `cor.vars` not specified, all numeric varibles used
ggstatsplot::ggcorrmat(data = 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,
  cor.vars = sleep_total:bodywt,
  cor.vars.names = c("total sleep", "REM sleep")
) + # further modification using `ggplot2`
  ggplot2::scale_y_discrete(position = "right")

# to get the correlation matrix
ggstatsplot::ggcorrmat(
  data = ggplot2::msleep,
  cor.vars = sleep_total:bodywt,
  output = "r"
)

# setting output = "p-values" (or "p") will return the p-value matrix
ggstatsplot::ggcorrmat(
  data = ggplot2::msleep,
  cor.vars = sleep_total:bodywt,
  corr.method = "r",
  p.adjust.method = "bonferroni",
  output = "p"
)

# setting `output = "ci"` will return the confidence intervals for unique
# correlation pairs
ggstatsplot::ggcorrmat(
  data = ggplot2::msleep,
  cor.vars = sleep_total:bodywt,
  p.adjust.method = "BH",
  output = "ci"
)

# modifying elements of the correlation matrix by changing function defaults
ggstatsplot::ggcorrmat(
  data = datasets::iris,
  cor.vars = c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width),
  sig.level = 0.01,
  ggtheme = ggplot2::theme_bw(),
  hc.order = TRUE,
  matrix.type = "lower",
  outline.col = "white",
  title = "Dataset: Iris"
)
# }

Documentation reproduced from package ggstatsplot, version 0.1.4, License: GPL-3 | file LICENSE

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