CRAN/E | recmetrics

recmetrics

Psychometric Evaluation Using Relative Excess Correlations

Installation

About

Modern results of psychometric theory are implemented to provide users with a way of evaluating the internal structure of a set of items guided by theory. These methods are discussed in detail in VanderWeele and Padgett (2024) doi:10.31234/osf.io/rnbk5. The relative excess correlation matrices will, generally, have numerous negative entries even if all of the raw correlations between each pair of indicators are positive. The positive deviations of the relative excess correlation matrix entries help identify clusters of indicators that are more strongly related to one another, providing insights somewhat analogous to factor analysis, but without the need for rotations or decisions concerning the number of factors. A goal similar to exploratory/confirmatory factor analysis, but 'recmetrics' uses novel methods that do not rely on assumptions of latent variables or latent variable structures.

Citation recmetrics citation info
noah-padgett.github.io/recmetrics/

Key Metrics

Version 0.1.0
R ≥ 2.10
Published 2024-02-27 221 days ago
Needs compilation? no
License MIT
License File
CRAN checks recmetrics results

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Maintainer

Maintainer

R. Noah Padgett

Authors

R. Noah Padgett

aut / cre / cph

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 2.10

Imports

dplyr
lifecycle
magrittr
stats
tidyselect

Suggests

testthat ≥ 3.0.0