computeCorrelation | R Documentation |
Computes correlation matrix as well as corresponding p-values.
computeCorrelation(object, ...)
## S4 method for signature 'Correlation'
computeCorrelation(
object,
across = NULL,
methods_corr = "pearson",
verbose = TRUE,
...
)
## S4 method for signature 'Analysis'
computeCorrelation(
object,
across = NULL,
across_subset = NULL,
methods_corr = "pearson",
verbose = TRUE
)
object |
Any object for whose class a method has been defined. |
... |
Additional arguments given to |
across |
Character vector or NULL. If character, the name of the grouping variables that contain the group assignment across which analysis should be conducted. If NULL, no grouping is done. |
verbose |
Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.) |
If argument across
is NULL. All numeric variables are simply
correlated.
If across
is character: Prior to correlation, the data set is split into subsets for
each group a grouping variable contains. Then the variables are correlated separately
for each group. This is done for every grouping variable denoted in the input
vector of across.
Results can be retrieved or visualized by specifying the grouping
variable of interest in the across
argument and the group(s) of interest
with the across_subset
argument of the respective function.
Computation is conducted with Hmisc::rcorr()
.
The input object.
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