mokken (version 2.0)

check.iio: Check of Invariant Item Ordering Using Method Restscore

Description

Returns a list with results from the investigation of invariant item ordering using method restscore. For a complete description of this procedure see Ligtvoet et al. (2008).

Usage

check.iio(X, minvi = m * 0.03, minsize = default.minsize, alpha = .05)

Arguments

X

matrix or data frame of numeric data containing the responses of nrow(X) respondents to ncol(X) items. Missing values are not allowed

minvi

minimum size of a violation that is reported. By default minvi equals .03 times the number of item step response functions (m)

minsize

minimum size of a rest score group. By default minsize = $N/10$ if $N \geq 500$; minsize = $N/5 if$ $250 \leq N < 500$; and minsize = $\max(N/3,50)$ if $N < 250$

alpha

Nominal Type I error for t test. Default alpha - .05

Value

• VI
  A matrix: The first column gives the number of violations of IIO according the method restscore. If the number of violations is nonzero, then the item with the largest number of violations is removed. If two or more items have the maximum number of violations, then from those items the item producing the lowest value of Loevinger's H is removed. The second column shows the number of violations with one item removed, the third column shows the number of violations with two items removed, etc.
• items.removed
  List of the items removed in chronological order
• HT
  Coefficient HT for the remaining items

References

Ligtvoet, R., van der Ark, L. A. and Sijtsma (2008) Investigating an invariant item ordering for polytomously scored items. Manuscript submitted for publication. Sijtsma, K, and Molenaar, I. W. (2002) Introduction to nonparametric item response theory. Thousand Oaks, CA: Sage. Van der Ark, L. A. (2007). Mokken scale analysis in R. Journal of Statistical Software. http://www.jstatsoft.org

See Also

coefH, check.monotonicity, check.pmatrix, check.reliability, check.restscore

Examples

data(acl)            

Order <- acl[,41:50]               
check.iio(Order)                     

Autonomy <- acl[,91:100]
check.iio(Autonomy)