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 22 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

heatmaply  
Interactive Cluster Heat Maps Using 'plotly' and 'ggplot2'
Create interactive cluster 'heatmaps' that can be saved as a stand- alone HTML file, embedded in 'R ...
Download / Learn more Package Citations See dependency  
Countr  
Flexible Univariate Count Models Based on Renewal Processes
Flexible univariate count models based on renewal processes. The models may include covariates and ...
Download / Learn more Package Citations See dependency  
spider  
Species Identity and Evolution in R
Analysis of species limits and DNA barcoding data. Included are functions for generating important s ...
Download / Learn more Package Citations See dependency  
cnum  
Chinese Numerals Processing
Chinese numerals processing in R, such as conversion between Chinese numerals and Arabic numerals a ...
Download / Learn more Package Citations See dependency  
odns  
Access Scottish Health and Social Care Open Data
Allows potential users of Scottish Health and Social Care Open Data ( ...
Download / Learn more Package Citations See dependency  
jointseg  
Joint Segmentation of Multivariate (Copy Number) Signals
Methods for fast segmentation of multivariate signals into piecewise constant profiles and for gene ...
Download / Learn more Package Citations See dependency  

28,720

R Packages

247,686

Dependencies

75,677

Author Associations

28,721

Publication Badges

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