rcorr.adjust

print.rcorr.adjust

a numeric matrix or data frame, or an object of class <code>"rcorr.adjust"</code> to be printed.

<code>"pearson"</code> or <code>"spearman"</code>, depending upon the type of
  	correlations desired; the default is <code>"pearson"</code>.

type

how to handle missing data: <code>"complete.obs"</code>, the default, use only complete cases;
  	<code>"pairwise.complete.obs"</code>, use all cases with valid data for each pair.

This function uses the <code><a href="/link/rcorr?package=QCAGUI&version=1.8-4&to=Hmisc" rd-options="Hmisc" data-mini-rdoc="Hmisc::rcorr">rcorr</a></code> function in the <pkg>Hmisc</pkg> package
to compute matrices of Pearson or Spearman correlations along with
the pairwise p-values among the correlations. The p-values are corrected
for multiple inference using Holm's method (see <code><a href="/link/p.adjust?package=QCAGUI&version=1.8-4&to=stats" rd-options="stats" data-mini-rdoc="stats::p.adjust">p.adjust</a></code>).
Observations are filtered for missing data, and only complete observations are used.

htest

QCAGUI is a graphical user interface (GUI) for the QCA
        package, derived from R Commander.  Because QCA has little to
        do with statistics, the menus from Rcmdr were stripped down to
        the very basics.  In crisp sets QCA, data is binary therefore
        it is fairly decent to treat it as categorical (1 - presence; 0
        - absence).  In order to ease the primary analysis (e.g. tables
        of frequencies) and the creation of basic graphs, this package
        activates some menus that are not available in Rcmdr but for
        factors. Users should be aware, however, that QCAGUI is not a
        package for statistics; Rcmdr is better suited for this
        purpose.

rcorr.adjust: Compute Pearson or Spearman Correlations with p-Values

Description

Usage

Arguments

Value