mokken (version 3.0.4)

check.monotonicity: Check of Monotonicity

Description

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).

Usage

check.monotonicity(X, minvi = 0.03, minsize = default.minsize)

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

minsize

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

Value

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.

Details

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.

References

Junker, B.W., & Sijtsma, K. (2000). Latent and manifest monotonicity in item response models. Applied Psychological Measurement, 24, 65-81. https://doi.org/10.1177/01466216000241004

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. https://www.jstatsoft.org/article/view/v020i11

See Also

check.errors, check.iio, check.restscore, check.pmatrix, check.reliability, coefH, plot.monotonicity.class, summary.monotonicity.class

Examples

# NOT RUN {
data(acl)
Communality <- acl[,1:10]
monotonicity.list <- check.monotonicity(Communality)
plot(monotonicity.list)
summary(monotonicity.list)
# }