DFIT (version 1.0-3)

AseIrt: Calculates the asymptotic covariance matrices for item parameters according with the IRT model.

Description

Calculates the asymptotic covariance matrices for item parameters according with the IRT model.

Usage

AseIrt(itemParameters, distribution = "norm",
  distributionParameters = list(mean = 0, sd = 1), logistic = TRUE,
  sampleSize = 1, irtModel = "3pl", subdivisions = 5000)

Arguments

itemParameters

A matrix or vector containing the item difficulties.

distribution

A string character indicating the generic name for the assumed distribution. Defaults to 'norm' for normal distribution.

distributionParameters

A list of extra parameters for the distribution function.

logistic

A logical indicating whether the logistic or the normal metric should be used.

sampleSize

A value indicating the sample size.

irtModel

A string stating the IRT model for all items.

subdivisions

A numeric value stating the maximum number of subdivisions for adaptive quadrature.

Value

ase A list containing the asymptotic matrices for each item

References

Li, Y. & Lissitz, R. (2004). Applications of the analytically derived standard errors of Item Response Theory item parameter estimates. Journal of educational measurement, 41(2), 85--117. doi:10.1111/j.1745-3984.2004.tb01109.x

Examples

# NOT RUN {
# # Not run
# #
# # data(dichotomousItemParameters)
# # threePlAse <- list()
# # threePlAse[['focal']] <- AseIrt(itemParameters = dichotomousItemParameters[['focal']],
# #                                 logistic = TRUE, sampleSize = 500, irtModel = '3pl')
# # threePlAse[['reference']] <- AseIrt(itemParameters = dichotomousItemParameters[['reference']],
# #                                     logistic = TRUE, sampleSize = 500, irtModel = '3pl')

# }