MBESS Implements methods that useful in designing research 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 at this
point MBESS 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 <http://nd.edu/~kkelley/site/MBESS.html> for a detailed
list of those that have contributed and other details.
Please read the manual and visit the corresponding web site
for information on the capabilities of the
MBESS package. Feel free
to contact me if there is a feature you would like to see added if it would
complement the goals of the MBESS package.
Ken Kelley <KKelley@ND.Edu; http://www.nd.edu/~kkelley>
Maintainer: Ken Kelley <KKelley@ND.Edu; http://www.nd.edu/~kkelley>
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.