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MBESS

The MBESS R Package (Now on GitHub)

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Install

install.packages('MBESS')

Monthly Downloads

9,054

Version

4.9.2

License

GPL-2 | GPL-3

Maintainer

Ken Kelley

Last Published

September 19th, 2022

Functions in MBESS (4.9.2)

F.and.R2.Noncentral.Conversion

Conversion functions from noncentral noncentral values to their corresponding and vice versa, for those related to the F-test and R Square.
Gardner.LD

The Gardner learning data, which was used by L.R. Tucker
Cor.Mat.MM

Correlation matrix for Maruyama & McGarvey (1980) data set
HS

Complete Data Set of Holzinger and Swineford's (1939) Study
Cor.Mat.Lomax

Correlation matrix for Lomax (1983) data set
CFA.1

One-factor confirmatory factor analysis model
MBESS

MBESS
ci.c.ancova

Confidence interval for an (unstandardized) contrast in ANCOVA with one covariate
Variance.R2

Variance of squared multiple correlation coefficient
Expected.R2

Expected value of the squared multiple correlation coefficient
ci.cc

Confidence interval for the population correlation coefficient
ci.omega2

Confidence Interval for omega-squared (\(\omega^2\)) for between-subject fixed-effects ANOVA and ANCOVA designs (and partial omega-squared \(\omega^2_p\) for between-subject multifactor ANOVA and ANCOVA designs)
Sigma.2.SigmaStar

Construct a covariance matrix with specified error of approximation
ancova.random.data

Generate random data for an ANCOVA model
ci.R2

Confidence interval for the population squared multiple correlation coefficient
ci.pvaf

Confidence Interval for the Proportion of Variance Accounted for (in the dependent variable by knowing the levels of the factor)
ci.reliability

Confidence Interval for a Reliability Coefficient
ci.c

Confidence interval for a contrast in a fixed effects ANOVA
ci.R

Confidence interval for the multiple correlation coefficient
ci.cv

Confidence interval for the coefficient of variation
ci.sc

Confidence Interval for a Standardized Contrast in a Fixed Effects ANOVA
ci.smd

Confidence limits for the standardized mean difference.
ci.snr

Confidence Interval for the Signal-To-Noise Ratio
aipe.smd

Sample size planning for the standardized mean different from the accuracy in parameter estimation approach
ci.sc.ancova

Confidence interval for a standardized contrast in ANCOVA with one covariate
intr.plot

Regression Surface Containing Interaction
ci.smd.c

Confidence limits for the standardized mean difference using the control group standard deviation as the divisor.
ci.rmsea

Confidence interval for the population root mean square error of approximation
ci.sm

Confidence Interval for the Standardized Mean
intr.plot.2d

Plotting Conditional Regression Lines with Interactions in Two Dimensions
ci.src

Confidence Interval for a Standardized Regression Coefficient
mediation.effect.plot

Visualizing mediation effects
conf.limits.nc.chisq

Confidence limits for noncentral chi square parameters
conf.limits.nct

Confidence limits for a noncentrality parameter from a t-distribution
ci.rc

Confidence Interval for a Regression Coefficient
mr.cv

Minimum risk point estimation of the population coefficient of variation
ss.aipe.c

Sample size planning for an ANOVA contrast from the Accuracy in Parameter Estimation (AIPE) perspective
ss.aipe.R2.sensitivity

Sensitivity analysis for sample size planning with the goal of Accuracy in Parameter Estimation (i.e., a narrow observed confidence interval)
cor2cov

Correlation Matrix to Covariance Matrix Conversion
ci.reg.coef

Confidence interval for a regression coefficient
prof.salary

Cohen et. al. (2003)'s professor salary data set
mediation

Effect sizes and confidence intervals in a mediation model
s.u

Unbiased estimate of the population standard deviation
mediation.effect.bar.plot

Bar plots of mediation effects
ss.aipe.rmsea

Sample size planning for RMSEA in SEM
covmat.from.cfm

Covariance matrix from confirmatory (single) factor model.
signal.to.noise.R2

Signal to noise using squared multiple correlation coefficient
smd

Standardized mean difference
ss.aipe.cv.sensitivity

Sensitivity analysis for sample size planning given the Accuracy in Parameter Estimation approach for the coefficient of variation.
ci.srsnr

Confidence Interval for the Square Root of the Signal-To-Noise Ratio
ss.aipe.cv

Sample size planning for the coefficient of variation given the goal of Accuracy in Parameter Estimation approach to sample size planning
ss.aipe.rmsea.sensitivity

a priori Monte Carlo simulation for sample size planning for RMSEA in SEM
cv

Function to calculate the regular (which is also biased) estimate of the coefficient of variation or the unbiased estimate of the coefficient of variation.
ss.aipe.sem.path.sensitiv

a priori Monte Carlo simulation for sample size planning for SEM targeted effects
ss.aipe.sem.path

Sample size planning for SEM targeted effects
ss.aipe.rc.sensitivity

Sensitivity analysis for sample size planing from the Accuracy in Parameter Estimation Perspective for the unstandardized regression coefficient
ss.aipe.reg.coef

Sample size necessary for the accuracy in parameter estimation approach for a regression coefficient of interest
power.equivalence.md.plot

Plot power of Two One-Sided Tests Procedure (TOST) for Equivalence
power.equivalence.md

Power of Two One-Sided Tests Procedure (TOST) for Equivalence
theta.2.Sigma.theta

Compute the model-implied covariance matrix of an SEM model
conf.limits.ncf

Confidence limits for noncentral F parameters
ss.aipe.c.ancova

Sample size planning for a contrast in randomized ANCOVA from the Accuracy in Parameter Estimation (AIPE) perspective
ss.aipe.c.ancova.sensitivity

Sensitivity analysis for sample size planning for the (unstandardized) contrast in randomized ANCOVA from the Accuracy in Parameter Estimation (AIPE) Perspective
ss.aipe.src

sample size necessary for the accuracy in parameter estimation approach for a standardized regression coefficient of interest
ss.aipe.src.sensitivity

Sensitivity analysis for sample size planing from the Accuracy in Parameter Estimation Perspective for the standardized regression coefficient
ss.aipe.sc

Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized contrast in ANOVA
ss.aipe.smd

Sample size planning for the standardized mean difference from the Accuracy in Parameter Estimation (AIPE) perspective
transform_Z.r

Transform Fischer's Z into the scale of a correlation coefficient
ss.aipe.reg.coef.sensitivity

Sensitivity analysis for sample size planning from the Accuracy in Parameter Estimation Perspective for the (standardized and unstandardized) regression coefficient
power.density.equivalence.md

Density for power of two one-sided tests procedure (TOST) for equivalence
ss.aipe.smd.sensitivity

Sensitivity analysis for sample size given the Accuracy in Parameter Estimation approach for the standardized mean difference.
mr.smd

Minimum risk point estimation of the population standardized mean difference
ss.power.rc

sample size for a targeted regression coefficient
ss.power.reg.coef

sample size for a targeted regression coefficient
ss.aipe.sc.ancova

Sample size planning from the AIPE perspective for standardized ANCOVA contrasts
smd.c

Standardized mean difference using the control group as the basis of standardization
ss.aipe.R2

Sample Size Planning for Accuracy in Parameter Estimation for the multiple correlation coefficient.
ss.aipe.pcm

Sample size planning for polynomial change models in longitudinal study
ss.aipe.reliability

Sample Size Planning for Accuracy in Parameter Estimation for Reliability Coefficients.
ss.aipe.rc

Sample size necessary for the accuracy in parameter estimation approach for an unstandardized regression coefficient of interest
ss.aipe.crd.es

Find target sample sizes for the accuracy in standardized conditions means estimation in CRD
t.and.smd.conversion

Conversion functions for noncentral t-distribution
ss.power.pcm

Sample size planning for power for polynomial change models
ss.power.R2

Function to plan sample size so that the test of the squared multiple correlation coefficient is sufficiently powerful.
transform_r.Z

Transform a correlation coefficient (r) into the scale of Fischer's Z
ss.aipe.sm

Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean
ss.aipe.sc.ancova.sensitivity

Sensitivity analysis for the sample size planning method for standardized ANCOVA contrast
ss.aipe.sc.sensitivity

Sensitivity analysis for sample size planning for the standardized ANOVA contrast from the Accuracy in Parameter Estimation (AIPE) Perspective
ss.power.sem

Sample size planning for structural equation modeling from the power analysis perspective
var.ete

The Variance of the Estimated Treatment Effect at Selected Covariate Values in a Two-group ANCOVA.
ss.aipe.sm.sensitivity

Sensitivity analysis for sample size planning for the standardized mean from the Accuracy in Parameter Estimation (AIPE) Perspective
upsilon

This function implements the upsilon effect size statistic as described in Lachowicz, Preacher, & Kelley (in press) for mediation.
ss.aipe.crd

Find target sample sizes for the accuracy in unstandardized conditions means estimation in CRD
verify.ss.aipe.R2

Internal MBESS function for verifying the sample size in ss.aipe.R2
vit

Visualize individual trajectories
vit.fitted

Visualize individual trajectories with fitted curve and quality of fit