mirt (version 0.4.0)

itemfit: Item fit statistics

Description

itemfit calculates the Zh values from Drasgow, Levine and Williams (1985) for unidimensional and multidimensional models, or $\chi^2$ values for unidimensional models.

Usage

itemfit(x, type = "Zh", ngroups = 10,
    empirical.plot = NULL)

Arguments

x

a computed model object of class ExploratoryClass, ConfirmatoryClass, or MultipleGroupClass

type

a character specifying whether the Zh ('Zh') or $\chi^2$ ('X2') statistic should be computed. Not that 'X2' can only be used for unidimensional models

ngroups

the number of theta groupings to use when computing 'X2'. Cells that have any expected values less than 5 are dropped and the degrees of freedom are adjusted accordingly

empirical.plot

a single numeric value indicating which item to plot (via itemplot) and overlay with the empirical $\theta$ groupings. Only applicable when type = 'X2'. The default is NULL, therefore no plots are drawn

References

Drasgow, F., Levine, M. V., & Williams, E. A. (1985). Appropriateness measurement with polychotomous item response models and standardized indices. Journal of Mathematical and Statistical Psychology, 38, 67-86.

See Also

personfit

Examples

#make some data
set.seed(1234)
a <- matrix(rnorm(20),ncol=1)
d <- matrix(rnorm(20),ncol=1)
items <- rep('dich', 20)
data <- simdata(a,d, 2000, items)

x <- mirt(data, 1, SE = FALSE)
fit <- itemfit(x)
fit

itemfit(x, type = 'X2', empirical.plot = 1) #empirical item plot