| summary.monotonicity.class {mokken} | R Documentation |
Summarize monotonicity.class objects
Description
S3 Method for summary of objects of class monotonicity.class.
Summarizes checks of monotonicity
Usage
## S3 method for class 'monotonicity.class'
summary(object, ...)
Arguments
object |
list produced by |
... |
Optional parameters will be ignored |
Value
Matrix with ncol(X) rows and 10 columns,
showing for each item a summary of the violations of monotonicity:
itemH = Item-scalability coefficient;
#ac = number of active pairs that were investigated;
#vi = number of violations in which the item is involved;
#vi/#ac = propotion of active pairs that is involved in a violation;
maxvi = maximum violation;
sum = sum of all violations;
zmax = maximum z-value;
zsig = number of significant z-values;
crit = Crit value (Molenaar & Sijtsma, 2000, pp. 49, 74).
Author(s)
L. A. van der Ark L.A.vanderArk@uva.nl
References
Koopman, L., Zijlstra, B. J. H., & Van der Ark, L. A. (2023a). Assumptions and Properties of Two-Level Nonparametric Item Response Theory Models. Manuscript submitted for publication.
Koopman, L., Zijlstra, B. J. H., & Van der Ark, L. A. (2023b). Evaluating Model Fit in Two-Level Mokken Scale Analysis. Manuscript submitted for publication.
Mokken, R. J. (1971) A Theory and Procedure of Scale Analysis. De Gruyter.
Molenaar, I.W., & Sijtsma, K. (2000) User's Manual MSP5 for Windows [Software manual]. IEC ProGAMMA.
Sijtsma, K., & Molenaar, I. W. (2002) Introduction to nonparametric item response theory. Sage.
Van der Ark, L. A. (2007). Mokken scale analysis in R. Journal of Statistical Software. doi:10.18637/jss.v020.i11
See Also
check.monotonicity, plot.monotonicity.class
Examples
data(acl)
Communality <- acl[,1:10]
monotonicity.list <- check.monotonicity(Communality)
plot(monotonicity.list)
summary(monotonicity.list)
# Compute two-level fit statistics (Koopman et al., 2023a, 2023b)
data("autonomySupport")
dat <- autonomySupport[, -1]
groups <- autonomySupport[, 1]
autonomyMM <- check.monotonicity(dat, level.two.var = groups)
summary(autonomyMM)