recmetrics - Psychometric Evaluation Using Relative Excess Correlations
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.
