Bayesrel (version 0.1.0)

strel: calculate single test reliability estimates

Description

calculate Bayesian and frequentist single test reliability measures. Reported are Bayesian credible intervals (HDI) and frequentist confidence intervals (non parametric or parametric bootstrap). The estimates supported are Cronbach alpha, lambda2/4/6, the glb, and Mcdonald omega.

Usage

strel(x, estimates = c("alpha", "lambda2", "glb", "omega"),
  interval = 0.95, n.iter = 2000, n.burnin = 50, boot.n = 1000,
  omega.freq.method = "cfa", omega.fit = FALSE, n.obs = NULL,
  alpha.int.analytic = FALSE, bayes = TRUE, freq = TRUE,
  para.boot = FALSE, prior.samp = FALSE, item.dropped = FALSE)

Arguments

x

A dataset or covariance matrix

estimates

A character vector containing the estimands, we recommend using lambda4 with only a few items due to the computation time

interval

A number specifying the uncertainty interval

n.iter

A number for the iterations of the Gibbs Sampler

n.burnin

A number for the burnin in the Gibbs Sampler

boot.n

A number for the bootstrap samples

omega.freq.method

A character string for the method of frequentist omega, either pfa or cfa

omega.fit

A logical for calculating the fit of the single factor model

n.obs

A number for the sample observations when a covariance matrix is supplied and the factor model is calculated

alpha.int.analytic

A logical for calculating the alpha confidence interval analytically

bayes

A logical for calculating the Bayesian estimates

freq

A logical for calculating the frequentist estimates

para.boot

A logical for calculating the parametric bootstrap, the default is the non-parametric

prior.samp

A logical for calculating the prior distributions (necessary for plot functions)

item.dropped

A logical for calculating the if-item-dropped statistics

References

murphy2007Bayesrel lee2007Bayesrel

Examples

# NOT RUN {
summary(strel(cavalini, estimates = "lambda2"))
summary(strel(cavalini, estimates = "lambda2", item.dropped = TRUE))


# }