sjp.corr.Rd
Plot correlation matrix as ellipses or tiles.
sjp.corr(data, title = NULL, axis.labels = NULL, sort.corr = TRUE, decimals = 3, na.deletion = c("listwise", "pairwise"), corr.method = c("pearson", "spearman", "kendall"), geom.colors = "RdBu", wrap.title = 50, wrap.labels = 20, show.legend = FALSE, legend.title = NULL, show.values = TRUE, show.p = TRUE, p.numeric = FALSE)
data | Matrix with correlation coefficients as returned by the
|
---|---|
title | character vector, used as plot title. Depending on plot type and function,
will be set automatically. If |
axis.labels | character vector with labels used as axis labels. Optional argument, since in most cases, axis labels are set automatically. |
sort.corr | Logical, if |
decimals | Indicates how many decimal values after comma are printed when
the values labels are shown. Default is 3. Only applies when
|
na.deletion | Indicates how missing values are treated. May be either
|
corr.method | Indicates the correlation computation method. May be one of
|
geom.colors | user defined color for geoms. See 'Details' in |
wrap.title | numeric, determines how many chars of the plot title are displayed in one line and when a line break is inserted. |
wrap.labels | numeric, determines how many chars of the value, variable or axis labels are displayed in one line and when a line break is inserted. |
show.legend | logical, if |
legend.title | character vector, used as title for the plot legend. |
show.values | Logical, whether values should be plotted or not. |
show.p | Logical, adds significance levels to values, or value and variable labels. |
p.numeric | Logical, if |
(Insisibily) returns the ggplot-object with the complete plot (plot
) as well as the data frame that
was used for setting up the ggplot-object (df
) and the original correlation matrix
(corr.matrix
).
Required argument is either a data.frame
or a matrix with correlation coefficients
as returned by the cor
-function. In case of ellipses, the
ellipses size indicates the strength of the correlation. Furthermore,
blue and red colors indicate positive or negative correlations, where
stronger correlations are darker.
If data
is a matrix with correlation coefficients as returned by
the cor
-function, p-values can't be computed.
Thus, show.p
and p.numeric
only have an effect if data
is a data.frame
.
# create data frame with 5 random variables mydf <- data.frame(cbind(runif(10), runif(10), runif(10), runif(10), runif(10))) # plot correlation matrix sjp.corr(mydf)#>#> Warning: Removed 15 rows containing missing values (geom_text).# ------------------------------- # Data from the EUROFAMCARE sample dataset # ------------------------------- library(sjlabelled) data(efc) # retrieve variable and value labels varlabs <- get_label(efc) # create data frame vars.index <- c(1, 4, 15, 19, 20, 21, 22, 24, 25) mydf <- data.frame(efc[, vars.index]) colnames(mydf) <- varlabs[vars.index] # show legend sjp.corr(mydf, show.legend = TRUE)#>#> Warning: Removed 45 rows containing missing values (geom_text).# ------------------------------- # auto-detection of labels # ------------------------------- sjp.corr(efc[, vars.index])#>#> Warning: Removed 45 rows containing missing values (geom_text).