wrightMap: wrightMap: item-person maps

Description

This function allows the easy generation of `Wright Maps' (named after Ben Wright), also known as item-person maps. They are used to to display unidimensional and multidimensional assessment results. These maps represent simultaneously the proficiency distribution of respondents and the item difficulty parameters as estimated by a model of the Rasch family.

Usage

wrightMap(thetas, thresholds = NULL, item.side = itemModern, person.side = personHist
,  main.title = "Wright Map", min.logit.pad = 0.25, max.logit.pad = 0.25, min.l = NULL
, max.l = NULL, item.prop = 0.8, return.thresholds = TRUE, new.quartz = FALSE
, use.hist = NULL,...) 
# S3 method for CQmodel
plot(x, ...)

Arguments

The parameters documented here do not include many of the options included in the Wright Map family of functions. For graphical parameters, see item.side and person.side. For data handling, see item.person.data and CQmodel.

wrightMap parameters:

thetas: a vector, matrix or data frame of person parameter estimates. Can also be a character string specifying a ConQuest output file of person parameter estimates, or a CQmodel object. Will be sent to the function personData.
thresholds: matrix or data frame of item parameter estimates. Can also be a character string specifying a ConQuest show file. Will be sent to the function itemData.
item.side: function to use to draw the item side of the map. Currently included options are itemModern (default), itemClassic (for ConQuest-style Wright Maps) and itemHist. See item.side for details.
person.side: function to use to draw the person side of the map. Currently included options are personHist (default), to draw the person distribution as a histogram, and personDens, which draws a density plot. See person.side for details.
main.title: title of the Wright Map.
min.logit.pad: numeric value indicating how much of the lower end of the logit scale should be included in the plot.
max.logit.pad: numeric value indicating how much of the upper end of the logit scale should be included in the plot.
min.l: numeric value for fixing the lower end of the logit scale. It overrides the automatic detection of the range and the min.logit.pad correction.
max.l: numeric value for fixing the upper end of the logit scale. It overrides the automatic detection of the range and the max.logit.pad correction.
item.prop: numeric value greater than 0 and smaller than 1 indicating the proportion of the plot to be allocated to the item part of the Wright Map.
return.thresholds: logical. Determines whether the to return or not the numeric values used to position the parameters on the item side of the Wright Map. Enabled by default.
new.quartz: logical. Determines whether the wrightMap will be created on a new graphical device or if it will reuse one already open. By default is set to FALSE to avoid creating new devices.
use.hist: deprecated. Use the person.side parameter instead
...: Additional arguments to pass to personData, itemData, person.side, or item.side

wrightMap can also be called by passing a CQmodel object to plot:

x: CQmodel object to pass to plot

Author

David Torres Irribarra and Rebecca Freund

References

Wilson, M. (2005). Constructing measures: An item response modeling approach. Wright, B. D., & Stone, M. H. (1979). Best test design. Chicago: Mesa Press.

Examples

Run this code


# Plotting results of a unidimensional Rasch Model

## Mock results
  uni.proficiency <- rnorm(1000, mean =  -0.5, sd = 1)
  difficulties  <- sort( rnorm( 20))

## Default map
wrightMap( uni.proficiency, difficulties)

## Density version
wrightMap( uni.proficiency, difficulties, person.side = personDens)


# Plotting results of a multidimensional Rasch Model

## Mock results
  multi.proficiency <- data.frame(
    d1 = rnorm(1000, mean =  -0.5, sd = 1),
    d2 = rnorm(1000, mean =   0.0, sd = 1),
    d3 = rnorm(1000, mean =  +0.5, sd = 1))

  difficulties  <- sort( rnorm( 20))

dev.new(width=10, height=10)
wrightMap( multi.proficiency, difficulties)

# Plotting results of a unidimensional Rating Scale Model

## Mock results
  uni.proficiency <- rnorm(1000, mean =  -0.5, sd = 1)

  items.loc <- sort( rnorm( 20))
  thresholds <- data.frame(
    l1 = items.loc - 0.5 ,
    l2 = items.loc - 0.25,
    l3 = items.loc + 0.25,
    l4 = items.loc + 0.5)

wrightMap( uni.proficiency, thresholds)


  
    ####ConQuest integration###
  
  	fpath <- system.file("extdata", package="WrightMap")
  	
  	#Partial credit model:

	model1 <- CQmodel(p.est = file.path(fpath,"ex2.eap"), show = file.path(fpath,"ex2.shw"))
	wrightMap(model1) 
	
	# Rating scale model:
	model2 <- CQmodel(file.path(fpath,"ex2b.eap"), file.path(fpath,"ex2b-2.shw"))
	wrightMap(model2, label.items.row = 2) 
		
  # Complex model
	model3 <- CQmodel(file.path(fpath,"ex4a.mle"), file.path(fpath,"ex4a.shw")) 
	wrightMap(model3, min.logit.pad = -29, person.side = personDens)
	
	
  ### Skip CQmodel
	wrightMap(file.path(fpath,"ex2a.eap"), file.path(fpath,"ex2a.shw"), 
  label.items.row = 3)