wrightMap | R Documentation |
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.
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 class 'CQmodel'
plot(x, ...)
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 |
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 |
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 |
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 |
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 |
max.l |
numeric value for fixing the upper end of the logit scale. It overrides the automatic detection of the range and the |
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 |
use.hist |
deprecated. Use the |
... |
Additional arguments to pass to |
wrightMap can also be called by passing a CQmodel object to plot:
x |
CQmodel object to pass to plot |
David Torres Irribarra and Rebecca Freund
Wilson, M. (2005). Constructing measures: An item response modeling approach. Wright, B. D., & Stone, M. H. (1979). Best test design. Chicago: Mesa Press.
person.side
item.side
personData
itemData
# 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)
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