The MBESS R Package

Implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became more general and now contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <> for a detailed list of those that have contributed and other details.


Reference manual

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4.8.1 by Ken Kelley, 3 months ago

Browse source code at

Authors: Ken Kelley [aut, cre]

Documentation:   PDF Manual  

Task views: Psychometric Models and Methods

GPL-2 | GPL-3 license

Imports boot, lavaan, MASS, methods, mnormt, nlme, OpenMx, parallel, sem, semTools

Depends on stats

Suggests gsl

Imported by CoTiMA, MOTE, apa, apaTables, auRoc, cvcqv, iMediate, neatStats, predictionInterval, pwr2ppl, replicationInterval, tidycomm.

Suggested by miceadds, rosetta, ufs, yhat.

See at CRAN