corr.test

A second matrix or dataframe with the same number of rows as x

use="pairwise" is the default value and will do pairwise deletion of cases. use="complete" will select just complete cases.

method="pearson" is the default value.  The alternatives to be passed to cor are "spearman" and "kendall"

method

Although the cor function finds the correlations for a matrix, it does not report probability values. corr.test uses cor to find the correlations for either complete or pairwise data and reports the sample sizes and probability values as well.

multivariate

models

A number of routines for personality, psychometrics and
        experimental psychology.  Functions are primarily for scale
        construction using factor analysis, cluster analysis and
        reliability analysis, although others provide basic descriptive
        statistics. Item Response Theory is done using factor analysis
        of tetrachoric and polychoric correlations. Functions for
        simulating particular item and test structures are included.
        Several functions serve as a useful front end for structural
        equation modeling.  Graphical displays of path diagrams, factor
        analysis and structural equation models are created using basic
        graphics. Some of the functions are written to support a book
        on psychometrics as well as publications in personality
        research. For more information, see the
        personality-project.org/r webpage.

William Revelle

psych

Procedures for Psychological, Psychometric, and Personality
        Research

corr.test function

Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.

A general purpose toolbox for personality, psychometric theory and experimental psychology.   Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using  factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis.   Functions for simulating and testing particular item and test structures are included. Several functions  serve as a useful front end for structural equation modeling.  Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r> web page.

corr.test: Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.

Description

Usage

Arguments

Value

Details

See Also

Examples