The psych package has been developed at Northwestern University to include functions most useful for personality, psychometrics, and psychological research. Some of the functions (e.g., describe, pairs.panels, error.bars) are useful for basic descriptive analyses typical of a short research paper.

Psychometric applications include routines for Very Simple Structure (VSS), Item Cluster Analysis (ICLUST), as well as functions to do Schmid Leiman transformations, principal axes factor analysis, and to calculate reliability coefficients alpha, beta, and omega-h.

Functions to score dichotomous, polytomous, and multiple choice items are useful for classic item analysis.

A number of procedures have been developed as part of the Synthetic Aperture Personality Assessment (SAPA) project. These routines facilitate forming and analyzing composite scales equivalent to using the raw data but doing so by adding within and between cluster/scale item correlations. These functions include extracting clusters from factor loading matrices (factor2cluster), synthetically forming clusters from correlation matrices (cluster.cor), and finding multiple correlation from correlation matrices (mat.regress).

An additional set of functions generate simulated data to meet certain structural properties. item.sim creates simple structure data, circ.sim will produce circumplex structured data, item.dichot produces circumplex or simple structured data for dichotomous items. These item structures are useful for understanding the effects of skew, differential item endorsement on factor and cluster analytic soutions.

The extended user manual includes examples of graphic output and more extensive demonstrations.For a step by step tutorial in the use of the psych package and the base functions in R for basic personality research, see the guide for personality research.

Note: the most recent development version is available as a source file at the repository maintained at http:personality-project.org/r . That version will have removed the most recently discovered bugs (but perhaps introduced other, yet to be discovered ones).

More information about the use of some of the functions may be found in the book : An introduction to Psychometric Theory with Applications in R (under development) .
For more extensive discussion of the use of psych in particular and R in general, consult A short guide to R

Version of May 16, 2008

William Revelle

Department of Psychology

Northwestern University