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MBESS
The MBESS R Package (Now on GitHub)
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install.packages('MBESS')
Monthly Downloads
8,425
Version
4.8.0
License
GPL-2 | GPL-3
Maintainer
Ken Kelley
Last Published
August 5th, 2020
Functions in MBESS (4.8.0)
Search functions
HS
Complete Data Set of Holzinger and Swineford's (1939) Study
MBESS
MBESS
ci.cc
Confidence interval for the population correlation coefficient
Gardner.LD
The Gardner learning data, which was used by L.R. Tucker
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.
ci.pvaf
Confidence Interval for the Proportion of Variance Accounted for (in the dependent variable by knowing the levels of the factor)
Cor.Mat.Lomax
Correlation matrix for Lomax (1983) data set
CFA.1
One-factor confirmatory factor analysis model
ancova.random.data
Generate random data for an ANCOVA model
aipe.smd
Sample size planning for the standardized mean different from the accuracy in parameter estimation approach
ci.c
Confidence interval for a contrast in a fixed effects ANOVA
ci.c.ancova
Confidence interval for an (unstandardized) contrast in ANCOVA with one covariate
Sigma.2.SigmaStar
Construct a covariance matrix with specified error of approximation
ci.sm
Confidence Interval for the Standardized Mean
ci.rmsea
Confidence interval for the population root mean square error of approximation
ci.sc.ancova
Confidence interval for a standardized contrast in ANCOVA with one covariate
Variance.R2
Variance of squared multiple correlation coefficient
ci.smd.c
Confidence limits for the standardized mean difference using the control group standard deviation as the divisor.
ci.reg.coef
Confidence interval for a regression coefficient
ci.cv
Confidence interval for the coefficient of variation
ci.smd
Confidence limits for the standardized mean difference.
intr.plot.2d
Plotting Conditional Regression Lines with Interactions in Two Dimensions
ci.sc
Confidence Interval for a Standardized Contrast in a Fixed Effects ANOVA
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.
intr.plot
Regression Surface Containing Interaction
mediation
Effect sizes and confidence intervals in a mediation model
conf.limits.ncf
Confidence limits for noncentral F parameters
conf.limits.nct
Confidence limits for a noncentrality parameter from a t-distribution
ci.src
Confidence Interval for a Standardized Regression Coefficient
ci.rc
Confidence Interval for a Regression Coefficient
ci.snr
Confidence Interval for the Signal-To-Noise Ratio
ci.reliability
Confidence Interval for a Reliability Coefficient
cor2cov
Correlation Matrix to Covariance Matrix Conversion
mr.cv
Minimum risk point estimation of the population coefficient of variation
power.equivalence.md
Power of Two One-Sided Tests Procedure (TOST) for Equivalence
power.equivalence.md.plot
Plot power of Two One-Sided Tests Procedure (TOST) for Equivalence
covmat.from.cfm
Covariance matrix from confirmatory (single) factor model.
power.density.equivalence.md
Density for power of two one-sided tests procedure (TOST) for equivalence
mr.smd
Minimum risk point estimation of the population standardized mean difference
ss.aipe.c.ancova
Sample size planning for a contrast in randomized ANCOVA from the Accuracy in Parameter Estimation (AIPE) perspective
s.u
Unbiased estimate of the population standard deviation
ss.aipe.c
Sample size planning for an ANOVA contrast from the Accuracy in Parameter Estimation (AIPE) perspective
signal.to.noise.R2
Signal to noise using squared multiple correlation coefficient
ci.R
Confidence interval for the multiple correlation coefficient
Cor.Mat.MM
Correlation matrix for Maruyama & McGarvey (1980) data set
Expected.R2
Expected value of the squared multiple correlation coefficient
ss.aipe.R2
Sample Size Planning for Accuracy in Parameter Estimation for the multiple correlation coefficient.
ci.R2
Confidence interval for the population squared multiple correlation coefficient
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)
prof.salary
Cohen et. al. (2003)'s professor salary data set
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
smd
Standardized mean difference
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.reg.coef
Sample size necessary for the accuracy in parameter estimation approach for a regression coefficient of interest
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
ci.srsnr
Confidence Interval for the Square Root of the Signal-To-Noise Ratio
ss.aipe.reliability
Sample Size Planning for Accuracy in Parameter Estimation for Reliability Coefficients.
conf.limits.nc.chisq
Confidence limits for noncentral chi square parameters
ss.aipe.rmsea
Sample size planning for RMSEA in SEM
ss.aipe.src.sensitivity
Sensitivity analysis for sample size planing from the Accuracy in Parameter Estimation Perspective for the standardized regression coefficient
ss.aipe.sm
Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean
ss.aipe.sem.path.sensitiv
a priori Monte Carlo simulation for sample size planning for SEM targeted effects
ss.aipe.sc.ancova
Sample size planning from the AIPE perspective for standardized ANCOVA contrasts
ss.power.reg.coef
sample size for a targeted regression coefficient
ss.power.sem
Sample size planning for structural equation modeling from the power analysis perspective
ss.aipe.sc.ancova.sensitivity
Sensitivity analysis for the sample size planning method for standardized ANCOVA contrast
ss.aipe.sem.path
Sample size planning for SEM targeted effects
t.and.smd.conversion
Conversion functions for noncentral t-distribution
ss.power.pcm
Sample size planning for power for polynomial change models
ss.aipe.sc.sensitivity
Sensitivity analysis for sample size planning for the standardized ANOVA contrast from the Accuracy in Parameter Estimation (AIPE) Perspective
smd.c
Standardized mean difference using the control group as the basis of standardization
ss.power.R2
Function to plan sample size so that the test of the squared multiple correlation coefficient is sufficiently powerful.
theta.2.Sigma.theta
Compute the model-implied covariance matrix of an SEM model
mediation.effect.bar.plot
Bar plots of mediation effects
mediation.effect.plot
Visualizing mediation effects
ss.aipe.rmsea.sensitivity
a priori Monte Carlo simulation for sample size planning for RMSEA in SEM
vit.fitted
Visualize individual trajectories with fitted curve and quality of fit
ss.power.rc
sample size for a targeted regression coefficient
verify.ss.aipe.R2
Internal MBESS function for verifying the sample size in ss.aipe.R2
ss.aipe.sc
Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized contrast in ANOVA
ss.aipe.sm.sensitivity
Sensitivity analysis for sample size planning for the standardized mean from the Accuracy in Parameter Estimation (AIPE) Perspective
ss.aipe.rc
Sample size necessary for the accuracy in parameter estimation approach for an unstandardized regression coefficient of interest
ss.aipe.cv.sensitivity
Sensitivity analysis for sample size planning given the Accuracy in Parameter Estimation approach for the coefficient of variation.
ss.aipe.pcm
Sample size planning for polynomial change models in longitudinal study
vit
Visualize individual trajectories
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
ss.aipe.crd.es
Find target sample sizes for the accuracy in standardized conditions means estimation in CRD
ss.aipe.rc.sensitivity
Sensitivity analysis for sample size planing from the Accuracy in Parameter Estimation Perspective for the unstandardized regression coefficient
var.ete
The Variance of the Estimated Treatment Effect at Selected Covariate Values in a Two-group ANCOVA.
ss.aipe.smd
Sample size planning for the standardized mean difference from the Accuracy in Parameter Estimation (AIPE) perspective
ss.aipe.smd.sensitivity
Sensitivity analysis for sample size given the Accuracy in Parameter Estimation approach for the standardized mean difference.
transform_Z.r
Transform Fischer's
Z
into the scale of a correlation coefficient
ss.aipe.src
sample size necessary for the accuracy in parameter estimation approach for a standardized regression coefficient of interest
transform_r.Z
Transform a correlation coefficient (r) into the scale of Fischer's
Z