mirt (version 0.4.2)

itemfit: Item fit statistics

Description

itemfit calculates the Zh values from Drasgow, Levine and Williams (1985) and $\chi^2$ values for unidimensional models. For Rasch models infit and outfit statistics are also produced.

Usage

itemfit(x, X2 = FALSE, group.size = 150,
    empirical.plot = NULL, method = "EAP")

Arguments

x

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

X2

logical; calculate the X2 statistic for unidimensional models?

group.size

approximate size of each group to be used in calculating the $\chi^2$ statistic

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

method

type of factor score estimation method. Can be expected a-posteriori ("EAP"), Bayes modal ("MAP"), weighted likelihood estimation ("WLE"), or maximum likelihood ("ML")

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.

Reise, S. P. (1990). A comparison of item- and person-fit methods of assessing model-data fit in IRT. Applied Psychological Measurement, 14, 127-137.

See Also

personfit

Examples

#make some data
set.seed(1234)
a <- matrix(rlnorm(20, meanlog=0, sdlog = .1),ncol=1)
d <- matrix(rnorm(20),ncol=1)
items <- rep('dich', 20)
data <- simdata(a,d, 2000, items)

x <- mirt(data, 1)
raschfit <- mirt(data, 1, itemtype='Rasch')
fit <- itemfit(x)
fit

itemfit(x, empirical.plot = 1) #empirical item plot
itemfit(raschfit, method = 'ML') #infit and outfit stats (method='ML' agrees better with eRm package)