check.monotonicity | R Documentation |
Returns a list (of class monotonicity.class
) with results from the investigation of monotonicity (Junker & Sijtsma, 2000; Mokken, 1971; Molenaar & Sijtsma, 2000; Sijtsma & Molenaar, 2002).
For two-level test data (clustered respondents) argument level.two.var exist, such that two lists are returned, containing the results for level 1 (person level) and level 2 (cluster level), respectively. Only method MIIO is implemented for two-level test data.
check.monotonicity(X, minvi = 0.03, minsize = default.minsize, level.two.var = NULL)
X |
matrix or data frame of numeric data
containing the responses of |
minvi |
minimum size of a violation that is reported |
minsize |
minimum size of a rest score group. By default
|
level.two.var |
Add respondent-clustering variable to get results for Level 1 (person level) and Level 2 (cluster level; see Koopman et al., 2023a,b) |
.
The output is of class monotonicity.class, and is often numerous.
Functions plot
and summary
can be used to summarize the output.
See Van der Ark (2007) for an example.
results |
A list with as many components as there are items. Each component itself is also a list containing the results of the check of monotonicity. |
I.labels |
The item labels |
Hi |
The item scalability coefficients Hi |
m |
The number of answer categories. |
L. A. van der Ark L.A.vanderArk@uva.nl
Junker, B.W., & Sijtsma, K. (2000). Latent and manifest monotonicity in item response models. Applied Psychological Measurement, 24, 65-81. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/01466216000241004")}
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v020.i11")}
check.errors
,
check.iio
,
check.restscore
,
check.pmatrix
,
check.reliability
,
coefH
,
plot.monotonicity.class
,
summary.monotonicity.class
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)
plot(autonomyMM)
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