Other packages > Find by keyword >

MBESS  

The MBESS R Package
View on CRAN: Click here


Download and install MBESS package within the R console
Install from CRAN:
install.packages("MBESS")

Install from Github:
library("remotes")
install_github("cran/MBESS")

Install by package version:
library("remotes")
install_version("MBESS", "4.9.42")



Attach the package and use:
library("MBESS")
Maintained by
Ken Kelley
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2006-05-06
Latest Update: 2025-07-25
Description:
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.
How to cite:
Ken Kelley (2006). MBESS: The MBESS R Package. R package version 4.9.42, https://cran.r-project.org/web/packages/MBESS. Accessed 02 Sep. 2026.
Previous versions and publish date:
0.0.1 (2006-05-06 14:30), 0.0.2 (2006-05-11 09:17), 0.0.3 (2006-05-29 09:49), 0.0.4 (2006-06-16 16:04), 0.0.5 (2006-07-19 18:01), 0.0.7 (2006-08-22 12:10), 0.0.8 (2006-12-04 22:00), 0.0.9 (2007-06-02 18:39), 1.0.0 (2007-12-07 09:41), 1.0.1 (2008-02-16 16:15), 2.0.0 (2008-11-24 20:54), 3.0.0 (2010-05-01 17:59), 3.0.1 (2010-05-05 10:08), 3.0.2 (2010-10-01 10:45), 3.0.3 (2010-10-07 13:25), 3.1.0 (2010-10-26 14:10), 3.1.1 (2010-11-07 09:22), 3.2.0 (2010-11-22 08:50), 3.2.1 (2012-08-31 16:00), 3.3.2 (2012-09-03 07:08), 3.3.3 (2012-12-17 06:09), 4.0.0 (2016-02-17 16:15), 4.1.0 (2016-09-23 22:40), 4.2.0 (2017-01-27 10:17), 4.3.0 (2017-06-06 18:00), 4.4.0 (2017-09-22 18:13), 4.4.1 (2017-11-01 08:39), 4.4.2 (2017-12-19 21:22), 4.4.3 (2018-01-11 00:37), 4.5.0 (2019-05-14 18:10), 4.5.1 (2019-05-17 15:40), 4.6.0 (2019-06-12 22:30), 4.7.0 (2020-05-15 22:30), 4.8.0 (2020-08-05 06:50), 4.8.1 (2021-10-16 16:50), 4.9.0 (2022-02-09 18:30), 4.9.1 (2022-07-11 14:20), 4.9.2 (2022-09-19 18:06), 4.9.3 (2023-10-26 09:10), 4.9.41 (2025-07-25 17:30), 4.9.42 (2026-01-08 07:11), 5.0.0 (2026-06-01 13:20), (2026-07-09 08:08)
Other packages that cited MBESS R package
View MBESS citation profile
Other R packages that MBESS depends, imports, suggests or enhances
Complete documentation for MBESS
Functions, R codes and Examples using the MBESS R package
Some associated functions: CFA.1 . Cor.Mat.Lomax . Cor.Mat.MM . Expected.R2 . F.and.R2.Noncentral.Conversion . Gardner.LD . HS . MBESS-package . Sigma.2.SigmaStar . Variance.R2 . aipe.smd . ancova.random.data . ci.R . ci.R2 . ci.c.ancova . ci.c . ci.cc . ci.cv . ci.omega2 . ci.pvaf . ci.rc . ci.reg.coef . ci.reliability . ci.rmsea . ci.sc.ancova . ci.sc . ci.sm . ci.smd.c . ci.smd . ci.snr . ci.src . ci.srsnr . conf.limits.nc.chisq . conf.limits.ncf . conf.limits.nct . cor2cov . covmat.from.cfm . cv . intr.plot.2d . intr.plot . mediation.effect.bar.plot . mediation.effect.plot . mediation . mr.cv . mr.smd . power.density.equivalence.md . power.equivalence.md . power.equivalence.md.plot . prof.salary . s.u . signal.to.noise.R2 . smd.c . smd . ss.aipe.R2 . ss.aipe.R2.sensitivity . ss.aipe.c.ancova . ss.aipe.c.ancova.sensitivity . ss.aipe.c . ss.aipe.cv . ss.aipe.cv.sensitivity . ss.aipe.pcm . ss.aipe.rc . ss.aipe.rc.sensitivity . ss.aipe.reg.coef . ss.aipe.reg.coef.sensitivity . ss.aipe.reliability . ss.aipe.rmsea . ss.aipe.rmsea.sensitivity . ss.aipe.sc.ancova . ss.aipe.sc.ancova.sensitivity . ss.aipe.sc . ss.aipe.sc.sensitivity . ss.aipe.sem.path . ss.aipe.sem.path.sensitiv . ss.aipe.sm . ss.aipe.sm.sensitivity . ss.aipe.smd . ss.aipe.smd.sensitivity . ss.aipe.src . ss.aipe.src.sensitivity . ss.power.R2 . ss.power.pcm . ss.power.rc . ss.power.reg.coef . ss.power.sem . ssAIPECRD . ssAIPECRDES . t.and.smd.conversion . theta.2.Sigma.theta . transform_Z.r . transform_r.Z . upsilon . var.ete . verify.ss.aipe.R2 . vit.fitted . vit . 
Some associated R codes: CFA.1.R . Expected.R2.R . F2Rsquare.R . Lambda2Rsquare.R . Rsquare2F.R . Rsquare2Lambda.R . Sigma.2.SigmaStar.R . Variance.R2.R . ancova.random.data.R . ci.R.R . ci.R2.R . ci.c.R . ci.c.ancova.R . ci.cc.R . ci.cv.R . ci.omega2.R . ci.pvaf.R . ci.rc.R . ci.reg.coef.R . ci.reliability.R . ci.rmsea.R . ci.sc.R . ci.sc.ancova.R . ci.sm.R . ci.smd.R . ci.smd.c.R . ci.snr.R . ci.src.R . ci.srsnr.R . conf.limits.nc.chisq.R . conf.limits.ncf.R . conf.limits.nct.R . cor2cov.R . covmat.from.cfm.R . cv.R . delta2lambda.R . intr.plot.2d.R . intr.plot.R . lambda2delta.R . mediation.R . mediation.effect.bar.plot.R . mediation.effect.plot.R . mr.cv.R . mr.smd.R . power.density.equivalence.md.R . power.equivalence.md.R . power.equivalence.md.plot.R . s.u.R . signal.to.noise.R2.R . smd.R . smd.c.R . ss.aipe.R2.R . ss.aipe.R2.sensitivity.R . ss.aipe.c.R . ss.aipe.c.ancova.R . ss.aipe.c.ancova.sensitivity.R . ss.aipe.cv.R . ss.aipe.cv.sensitivity.R . ss.aipe.pcm.R . ss.aipe.rc.R . ss.aipe.rc.sensitivity.R . ss.aipe.reg.coef.R . ss.aipe.reg.coef.sensitivity.R . ss.aipe.reliability.R . ss.aipe.rmsea.R . ss.aipe.rmsea.sensitivity.R . ss.aipe.sc.R . ss.aipe.sc.ancova.R . ss.aipe.sc.ancova.sensitivity.R . ss.aipe.sc.sensitivity.R . ss.aipe.sem.path.R . ss.aipe.sem.path.sensitiv.R . ss.aipe.sm.R . ss.aipe.sm.sensitivity.R . ss.aipe.smd.R . ss.aipe.smd.full.R . ss.aipe.smd.lower.R . ss.aipe.smd.sensitivity.R . ss.aipe.smd.upper.R . ss.aipe.src.R . ss.aipe.src.sensitivity.R . ss.power.R2.R . ss.power.pcm.R . ss.power.rc.R . ss.power.reg.coef.R . ss.power.sem.R . theta.2.Sigma.theta.R . transform_Z.r.R . transform_r.Z.R . upsilon.R . var.ete.R . verify.ss.aipe.R2.R . vit.R . vit.fitted.R . widthsscrd.R .  Full MBESS package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

VIM  
Visualization and Imputation of Missing Values
New tools for the visualization of missing and/or imputed values are introduced, which can be used f ...
Download / Learn more Package Citations See dependency  
recmap  
Compute the Rectangular Statistical Cartogram
Implements the RecMap MP2 construction heuristic . This algorithm draw ...
Download / Learn more Package Citations See dependency  
ggsci  
Scientific Journal and Sci-Fi Themed Color Palettes for 'ggplot2'
A collection of 'ggplot2' color palettes inspired by plots in scientific journals, data visualizati ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
multicmp  
Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution
A toolkit containing statistical analysis models motivated by multivariate forms of the Conway-Maxwe ...
Download / Learn more Package Citations See dependency  

28,437

R Packages

239,283

Dependencies

75,283

Author Associations

28,438

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA