ds.hetcor.RdThis function is based on the hetcor function from the R package polycor.
ds.hetcor(
data = NULL,
ML = TRUE,
std.err = TRUE,
bins = 4,
pd = TRUE,
use = "complete.obs",
datasources = NULL
)the name of a data frame consisting of factors, ordered factors, logical variables, character variables, and/or numeric variables, or the first of several variables.
if TRUE, compute maximum-likelihood estimates; if FALSE (default), compute quick two-step estimates.
if TRUE (default), compute standard errors.
number of bins to use for continuous variables in testing bivariate normality; the default is 4.
if TRUE (default) and if the correlation matrix is not positive-definite, an attempt will be made to adjust it to a positive-definite matrix, using the nearPD function in the Matrix package. Note that default arguments to nearPD are used (except corr=TRUE); for more control call nearPD directly.
if "complete.obs", remove observations with any missing data; if "pairwise.complete.obs", compute each correlation using all observations with valid data for that pair of variables.
a list of DSConnection-class objects obtained after login.
If the datasources argument is not specified the default set of connections will be
used: see datashield.connections_default.
Returns an object of class "hetcor" from each study, with the following components: the correlation matrix; the type of each correlation: "Pearson", "Polychoric", or "Polyserial"; the standard errors of the correlations, if requested; the number (or numbers) of observations on which the correlations are based; p-values for tests of bivariate normality for each pair of variables; the method by which any missing data were handled: "complete.obs" or "pairwise.complete.obs"; TRUE for ML estimates, FALSE for two-step estimates.
Computes a heterogenous correlation matrix, consisting of Pearson product-moment correlations between numeric variables, polyserial correlations between numeric and ordinal variables, and polychoric correlations between ordinal variables.