Methods for the Behavioral, Educational, and Social Sciences


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Documentation for package `MBESS'

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ci.cv Confidence interval for the coefficient of variation
ci.R2 Confidence intervals for the squared multiple correlation coefficient
ci.reg.coef confidence interval for a regression coefficient
ci.smd Confidence limits for the standardized mean difference.
ci.smd.c Confidence limits for the standardized mean difference using the control group standard deviation as the divisor.
conf.limits.nc.chisq Confidence limits for noncentral chi square parameters
conf.limits.ncf Confidence limits for noncentral F parameters
conf.limits.nct Confidence limits for a noncentrality parameter from a t-distribution
conf.limits.nct.M1 Confidence limits for a noncentrality parameter from a t-distribution (Method 1 of 3)
conf.limits.nct.M2 Confidence limits for a noncentrality parameter from a t-distribution (Method 2 of 3)
conf.limits.nct.M3 Confidence limits for a noncentrality parameter from a t-distribution (Method 3 of 3)
cv Function to calculate the regular (and biased) estimate of the coefficient of variation or the unbiased estimate of the coefficient of variation.
delta2lambda Conversion functions for noncentral t-distribution
Expected.R2 Expected value of the squared multiple correlation coefficient
F2Rsquare 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
lambda2delta Conversion functions for noncentral t-distribution
Lambda2Rsquare Conversion functions from noncentral noncentral values to their corresponding and vice versa, for those related to the F-test and R Square.
MBES Methods for the Behavioral, Educational, and Social Sciences
mbes Methods for the Behavioral, Educational, and Social Sciences
MBESS Methods for the Behavioral, Educational, and Social Sciences
mbess Methods for the Behavioral, Educational, and Social Sciences
Rsquare2F Conversion functions from noncentral noncentral values to their corresponding and vice versa, for those related to the F-test and R Square.
Rsquare2Lambda Conversion functions from noncentral noncentral values to their corresponding and vice versa, for those related to the F-test and R Square.
s.u Unbiased estiamte for the standard deviation
signal.to.noise.R2 Signal to noise using squared multiple correlation coefficient
smd Standardized mean difference
smd.c Standardized mean difference using the control group as the basis of standardization
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.cv.sensitivity Sensitivity analysis for sample size planning given the Accuracy in Parameter Estimation approach for the coefficient of variation.
ss.aipe.R2 Sample Size Planning for Accuracy in Parameter Estimation (i.e., precision) for the 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)
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 planing from the Accuracy in Parameter Estimation Perspective for the (standardized and unstandardized) regression coefficient
ss.aipe.smd Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean difference
ss.aipe.smd.full Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean difference
ss.aipe.smd.lower Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean difference
ss.aipe.smd.sensitivity Sensitivity analysis for sample size given the Accuracy in Parameter Estimation approach for the standardized mean difference.
ss.aipe.smd.upper Sample size planning for Accuracy in Parameter Estimation (AIPE) of the standardized mean difference
ss.power.R2 Function to plan sample size so that the test of the squred multiple correlation coefficient is sufficiently powerful.
ss.power.reg.coef sample size for a targeted regression coefficient
Variance.R2 Variance of squared multiple correlation coefficient
verify.ss.aipe.R2 Internal MBESS function for verifying the sample size in ss.aipe.R2
vit Visualize individual trajectories