plot.pwrrasch: Plot Statistical Power Curve

In pwrRasch: Statistical Power Simulation for Testing the Rasch Model

Description

Generic plot function for the pwrrasch object, which plots the statistical power curve relating statistical power to sample size

Usage

## S3 method for class 'pwrrasch'
plot(x, plot.sig.level = TRUE, type = c("b", "b"),
  pch = c(19, 17), lty = c(1, 3), lwd = c(1, 1), legend = "topleft",
  bty = "o", ...)

Arguments

x	pwrrasch object.
plot.sig.level	If TRUE, nominal significance level is plotted.
type	Vector indicating type of plot for the statistica power curve and the type 1 risk curve.
pch	Vector indicating plotting symbol for the statistical power curve and the type 1 risk curve.
lty	Vector indicating line type for the statistical power curve and the type 1 risk curve.
lwd	Vector indicating line width for the statistical power curve and the type 1 risk curve.
legend	Location of the legend. If FALSE, legend is omitted.
bty	Type of box to be drawn around the legend.
...	Additional arguments affecting the summary produced.

Details

Graphical parameters are:

• type The following values are possible: "p" for points, "l" for lines, "b" for both point and lines

• pch see points

• lty Line types can be specified as an integer (0 = blank, 1 = solid, 2 = dashed, 3 = dotted, 4 = dotdash, 5 = longdash, 6 = twodash)

• lwd Positive numbers indicating line widths

• legend Either the x and y coordinates to be used to position the legend or keyword from the list "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right" and "center"

• bty Allowed values are "o" (draw box around legend) and "n" (do not draw box around legend).

Author(s)

Takuya Yanagida [e-mail], Jan Steinfeld [e-mail]

References

Kubinger, K. D., Rasch, D., & Yanagida, T. (2009). On designing data-sampling for Rasch model calibrating an achievement test. Psychology Science Quarterly, 51, 370-384.

Kubinger, K. D., Rasch, D., & Yanagida, T. (2011). A new approach for testing the Rasch model. Educational Research and Evaluation, 17, 321-333.

Examples

## Not run: 

# item parameters
ipar2 <- ipar1 <- seq(-3, 3, length.out = 20)
# model differential item function (DIF)
ipar2[10] <- ipar1[11]
ipar2[11] <- ipar1[10]
# simulation for b = 100, 200, 300, 400, 500
simres <- pwr.rasch(seq(100, 500, by = 100), ipar = list(ipar1, ipar2))
plot(simres)

## End(Not run)

pwrRasch documentation built on May 1, 2019, 10:37 p.m.