plot.iio.class {mokken}

Plot iio.class objects

Description

S3 Method to plot objects of class iio.class. Graphic display of the checks of iio. One graph for each item plotting the estimated item response functions.

Usage

## S3 method for class 'iio.class'
plot(x, item.pairs = all.pairs, ci = TRUE, alpha = .05, 
       color = c("black", "blue"), transparancy = 20, ask = TRUE, ...)

Arguments

x

Object of class iio.class produced by check.iio.

item.pairs

vector containing the numbers of the item pairs for which the results are depicted graphically. For example, item.pairs = 1 prints the results for items 1 and 2, item.pairs = 2 prints the results for items 1 and 3, item.pairs = J prints the results for items 1 and $J$, and item.pairs = J+1 prints the results for items 2 and 3. Default the results for all item pairs are depicted.

ci

Boolean. If TRUE (default), then confidence envelops are plotted around IRFs.

alpha

Type of plotted (1 - alpha) confidence intervals. By default 95-percent confidence intervals are depicted

color

Color of the plotted curves and confidence envelops. Defaults are black for the first item and blue for the second item.

transparancy

Transparancy of the confidence intervals. Higher values result in more opaque colors for the confidence intervals.

ask

Boolean. If TRUE (default), then par("ask"=TRUE); i.e., a hard return between subsequent plots is required. If FALSE, then par("ask"=FALSE).

...

Optional graphical parameters will be ignored

Details

The plot function corresponds to method MIIO; each graph plots the estimated item response functions (item rest-score functions) for two items. For details of the method, see Ligtvoet et al. (2010, 2011); Sijtsma et al. (2012). For details of the confidence envelopes, see Van der Ark (2012b). For the implementation in R, see Van der Ark (2012a). For ask==FALSE, the default graphic device in R may only display the last graph.

Value

Returns a graph.

Author(s)

L. A. van der Ark [e-mail]

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.

Ligtvoet, R., L. A. van der Ark, J. M. te Marvelde, & K. Sijtsma (2010). Investigating an invariant item ordering for polytomously scored items. Educational and Psychological Measurement, 70, 578-595. doi:10.1177/0013164409355697

Ligtvoet, R., L. A. van der Ark, W. P. Bergsma, & K. Sijtsma (2011). Polytomous latent scales for the investigation of the ordering of items. Psychometrika, 76, 200-216. doi:10.1007/s11336-010-9199-8

Sijtsma, K., R. R. Meijer, & Van der Ark, L. A. (2011). Mokken scale analysis as time goes by: An update for scaling practitioners. Personality and Individual Differences, 50, 31-37. doi:10.1016/j.paid.2010.08.016

Van der Ark, L. A. (2012). New developjements in Mokken scale analysis in R. Journal of Statistical Software, 48 (5), 1-27. doi:10.18637/jss.v048.i05

Van der Ark, L. A. (2014). Visualizing uncertainty of estimated response functions in nonparametric item response theory. In R. E. Millsap, L. A. van der Ark, D. Bolt, & C. M. Woods (Eds.), New developments in quantitative psychology (pp. 59-68). New York: Springer. doi:10.1007/978-1-4614-9348-8_5

See Also

check.iio, summary.iio.class

Examples

data(acl)
Communality <- acl[,1:10]
iio.list <- check.iio(Communality)
summary(iio.list)
plot(iio.list)

# Compute two-level fit statistics (Koopman et al., 2023a, 2023b)
data("autonomySupport")
dat <- autonomySupport[, -1]
groups <- autonomySupport[, 1]
autonomyMIIO <- check.iio(dat, item.selection = FALSE, level.two.var = groups)
summary(autonomyMIIO)
plot(autonomyMIIO)