R/grouped_ggcorrmat.R
grouped_ggcorrmat.Rd
Helper function for ggstatsplot::ggcorrmat
to apply this function across
multiple levels of a given factor and combining the resulting plots using
ggstatsplot::combine_plots2
.
grouped_ggcorrmat( data, cor.vars = NULL, cor.vars.names = NULL, grouping.var, title.prefix = NULL, output = "plot", ..., plotgrid.args = list(), title.text = NULL, title.args = list(size = 16, fontface = "bold"), caption.text = NULL, caption.args = list(size = 10), sub.text = NULL, sub.args = list(size = 12) )
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 |
cor.vars.names | Optional list of names to be used for |
grouping.var | A single grouping variable (can be entered either as a
bare name |
title.prefix | Character string specifying the prefix text for the fixed
plot title (name of each factor level) (Default: |
output | Character that decides expected output from this function. If
|
... | Arguments passed on to
|
plotgrid.args | A list of additional arguments to |
title.text | String or plotmath expression to be drawn as title for the combined plot. |
title.args | A list of additional arguments
provided to |
caption.text | String or plotmath expression to be drawn as the caption for the combined plot. |
caption.args | A list of additional arguments
provided to |
sub.text | The label with which the combined plot should be annotated. Can be a plotmath expression. |
sub.args | A list of additional arguments
provided to |
https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggcorrmat.html
# \donttest{ # for reproducibility set.seed(123) # for plot ggstatsplot::grouped_ggcorrmat( data = iris, grouping.var = Species, type = "robust", p.adjust.method = "holm" )# for dataframe ggstatsplot::grouped_ggcorrmat( data = ggplot2::msleep, grouping.var = vore, type = "bayes", output = "dataframe" )#> Warning: Series not converged.#> Warning: Series not converged.#> Warning: Series not converged.#> Warning: Series not converged.#> # A tibble: 60 x 14 #> vore parameter1 parameter2 estimate conf.low conf.high pd #> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 carni sleep_total sleep_rem 0.845 0.641 0.961 1 #> 2 carni sleep_total sleep_cycle 0.204 -0.351 0.764 0.698 #> 3 carni sleep_total awake -1.00 -1.00 -1.00 1 #> 4 carni sleep_total brainwt -0.382 -0.759 0.0549 0.895 #> 5 carni sleep_total bodywt -0.379 -0.662 -0.0654 0.960 #> 6 carni sleep_rem sleep_cycle 0.0548 -0.534 0.587 0.562 #> 7 carni sleep_rem awake -0.848 -0.962 -0.678 1 #> 8 carni sleep_rem brainwt -0.308 -0.760 0.252 0.804 #> 9 carni sleep_rem bodywt -0.371 -0.716 0.0694 0.899 #> 10 carni sleep_cycle awake -0.205 -0.754 0.373 0.690 #> rope.percentage prior.distribution prior.location prior.scale bayes.factor #> <dbl> <chr> <dbl> <dbl> <dbl> #> 1 0 cauchy 0 0.707 112. #> 2 0.168 cauchy 0 0.707 0.714 #> 3 0 cauchy 0 0.707 NA #> 4 0.116 cauchy 0 0.707 1.13 #> 5 0.078 cauchy 0 0.707 1.72 #> 6 0.206 cauchy 0 0.707 0.621 #> 7 0.0118 cauchy 0 0.707 112. #> 8 0.136 cauchy 0 0.707 0.848 #> 9 0.124 cauchy 0 0.707 1.03 #> 10 0.165 cauchy 0 0.707 0.714 #> method n.obs #> <chr> <int> #> 1 Bayesian Pearson 10 #> 2 Bayesian Pearson 5 #> 3 Bayesian Pearson 19 #> 4 Bayesian Pearson 9 #> 5 Bayesian Pearson 19 #> 6 Bayesian Pearson 5 #> 7 Bayesian Pearson 10 #> 8 Bayesian Pearson 6 #> 9 Bayesian Pearson 10 #> 10 Bayesian Pearson 5 #> # ... with 50 more rows# }