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, prnt.plot = TRUE)
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 
prnt.plot  logical, if 
(Insisibily) returns the ggplotobject with the complete plot (plot
) as well as the data frame that
was used for setting up the ggplotobject (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, pvalues 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)#>#  # 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)#>#  # autodetection of labels #  sjp.corr(efc[, vars.index])#>