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 the contributions of many people over the years, who are acknowledged in the package documentation.

MBESS

MBESS (pronounced 'em-bes') is an R package that implements methods useful in designing research studies and analyzing data, with particular emphasis on methods developed for or used within the behavioral, educational, and social sciences (broadly defined). Many of the methods, however, apply across a wide variety of disciplines.

MBESS was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences.' As the package became more general it became an orphan acronym: what was once an acronym is now literally its name.

Capabilities

MBESS provides suites of functions for:

• effect sizes (standardized and unstandardized);
• confidence intervals for effect sizes, including noncentral methods;
• sample size planning from the accuracy in parameter estimation (AIPE), power analytic, equivalence, and minimum risk point estimation perspectives;
• mediation analysis;
• properties of distributions; and
• a variety of utility functions.

See the help pages (for example, library(help = 'MBESS')) for the full list of functions.

Installation

Install the released version from CRAN:

install.packages('MBESS')

The development version is available on GitHub:

# install.packages('remotes')
remotes::install_github('yelleKneK/MBESS')

Citation

To cite MBESS in publications, run:

citation('MBESS')

The primary references are Kelley (2007, Behavior Research Methods, 39, 979-984) and Kelley (2007, Journal of Statistical Software, 20(8), 1-24).

Acknowledgments

MBESS has benefited from the contributions of many people. See the CONTRIBUTORS file that ships with the package, located via system.file('CONTRIBUTORS.md', package = 'MBESS').

Maintenance status

MBESS is mature, stable, and widely used, and it remains fully supported. Maintenance mode does not mean the package is finished or abandoned: MBESS will continue to be maintained so that it keeps working with current versions of R and its dependencies, and it will remain on CRAN. Existing code that relies on MBESS will keep working, so users can continue to depend on it with confidence.

New methodological development now happens in its successor package, DMAR (Design, Measurement, and Analysis in R), which is available on CRAN. DMAR is where new methods will appear, and MBESS and DMAR are designed to coexist, so there is no need to migrate existing work.

License

GPL-2 | GPL-3. Maintainer: Ken Kelley ([email protected]).