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