empirical_rxx: Function to calculate the empirical (marginal) reliability

View source: R/empirical_rxx.R

empirical_rxxR Documentation

Function to calculate the empirical (marginal) reliability

Description

Given secondary latent trait estimates and their associated standard errors returned from fscores, compute the empirical reliability.

Usage

empirical_rxx(Theta_SE, T_as_X = FALSE)

Arguments

Theta_SE

a matrix of latent trait estimates returned from fscores with the options full.scores = TRUE and full.scores.SE = TRUE

T_as_X

logical; should the observed variance be equal to var(X) = var(T) + E(E^2) or var(X) = var(T) when computing empirical reliability estimates? Default (FALSE) uses the former

Author(s)

Phil Chalmers rphilip.chalmers@gmail.com

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v048.i06")}

See Also

fscores, marginal_rxx

Examples


## Not run: 

dat <- expand.table(deAyala)
itemstats(dat)
mod <- mirt(dat)

theta_se <- fscores(mod, full.scores.SE = TRUE)
empirical_rxx(theta_se)

theta_se <- fscores(mod, full.scores.SE = TRUE, method = 'ML')
empirical_rxx(theta_se)
empirical_rxx(theta_se, T_as_X = TRUE)


## End(Not run)

mirt documentation built on Sept. 11, 2024, 7:14 p.m.