| marginal_rxx {mirt} | R Documentation |
Given an estimated model and a prior density function, compute the marginal reliability. This is only available for unidimensional tests.
marginal_rxx(mod, density = dnorm, theta_lim = c(-6, 6), ...)
mod |
an object of class |
density |
a density function to use for integration. Default assumes the latent traits are from a normal (Gaussian) distribution |
theta_lim |
a vector containing the range of integration |
... |
additional arguments passed to the density function |
Phil Chalmers rphilip.chalmers@gmail.com
empirical_rxx, extract.group, testinfo
## Not run: dat <- expand.table(deAyala) mod <- mirt(dat, 1) # marginal estimate marginal_rxx(mod) # empirical estimate (assuming the same prior) fscores(mod, returnER = TRUE) # empirical rxx the alternative way, given theta scores and SEs fs <- fscores(mod, full.scores.SE=TRUE) head(fs) empirical_rxx(fs) ## End(Not run)