Bayesian Test Reliability Estimation
bcor: Bayesian Estimation of The Correlation Matrix
bcov: Bayesian Estimation of the Variance Covariance Matrix
bomega: Bayesian Estimation of Coefficient Omega
bomega_general: Bayesian Estimation of Coefficient Omega, General Form
brxx_Cor: Bayesian Estimation of Reliability from Correlation
brxx_Cor_general: Bayesian Estimation of Reliability from Correlation,...
brxx_general: Bayesian Estimation of Reliability from Variance Estimat...
brxx_ICC: Bayesian Estimation of Reliability from ICC
brxx_ICC_general: Bayesian Estimation of Reliability from ICC, General...
prep: Prepare Data File for Bayesian Analysis
process: rotates and calulates reliability for Stan output
scree: Scree Plot with Pairwise Complete Cases
standardize: Standardization of Data Matrix
summarize: Summarize Stan output as median, SD, and HPD quantiles
unpack: Unpack Stan output for factor analysis samples from Stan
When samples contain missing data, are small, or are suspected of bias, estimation of scale reliability may not be trustworthy. A recommended solution for this common problem has been Bayesian model estimation. Bayesian methods rely on user specified information from historical data or researcher intuition to more accurately estimate the parameters. This package provides a user friendly interface for estimating test reliability. Here, reliability is modeled as a beta distributed random variable with shape parameters alpha=true score variance and beta=error variance (Tanzer & Harlow, 2020) <doi:10.1080/00273171.2020.1854082>.