Functionality for reliability estimates. For unidimensional tests:
Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower
bound and coefficient omega in a Bayesian and a frequentist version.
For multidimensional tests: omega-total and omega-hierarchical.
The results include confidence and credible intervals, the
probability of a coefficient being larger than a cutoff,
and a check for the factor models, necessary for the omega coefficients.
The method for the Bayesian unidimensional estimates, except for omega,
is sampling from the posterior inverse 'Wishart' for the
covariance matrix based measures (see 'Murphy', 2007,
<https://groups.seas.harvard.edu/courses/cs281/papers/murphy-2007.pdf>.
The Bayesian omegas (unidimensional, hierarchical, and total) are obtained by
'Gibbs' Sampling from the conditional posterior distributions of
(1) the single factor model and (2) the higher order factor model
('Lee', 2007, <doi:10.1002/9780470024737>).

Functionality for reliability estimates. For 'unidimensional' tests:
Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower
bound and coefficient omega_u ('unidimensional') in a Bayesian and a frequentist version.
For multidimensional tests: omega_t (total) and omega_h (hierarchical).
The results include confidence and credible intervals, the
probability of a coefficient being larger than a cutoff,
and a check for the factor models, necessary for the omega coefficients.
The method for the Bayesian 'unidimensional' estimates, except for omega_u,
is sampling from the posterior inverse 'Wishart' for the
covariance matrix based measures (see 'Murphy', 2007,
<https://groups.seas.harvard.edu/courses/cs281/papers/murphy-2007.pdf>.
The Bayesian omegas (u, t, and h) are obtained by
'Gibbs' sampling from the conditional posterior distributions of
(1) the single factor model and (2) the second-order factor model
('Lee', 2007, <https://onlinelibrary.wiley.com/doi/book/10.1002/9780470024737>).
LaplacesDemon, MASS, lavaan, coda, methods, stats, graphics,
progress, Rdpack, Rcpp (>= 1.0.4.6)