View source: R/class.accuracy.rasch.R
class.accuracy.rasch | R Documentation |
This function computes the classification accuracy in the Rasch model for the maximum likelihood (person parameter) estimate according to the method of Rudner (2001).
class.accuracy.rasch(cutscores, b, meantheta, sdtheta, theta.l, n.sims=0)
cutscores |
Vector of cut scores |
b |
Vector of item difficulties |
meantheta |
Mean of the trait distribution |
sdtheta |
Standard deviation of the trait distribution |
theta.l |
Discretized theta distribution |
n.sims |
Number of simulated persons in a data set. The default is 0 which means that no simulation is performed. |
A list with following entries:
class.stats |
Data frame containing classification accuracy statistics. The
column |
class.prob |
Probability table of classification |
Rudner, L.M. (2001). Computing the expected proportions of misclassified examinees. Practical Assessment, Research & Evaluation, 7(14).
Classification accuracy of other IRT models can be obtained with the R package cacIRT.
############################################################################# # EXAMPLE 1: Reading dataset ############################################################################# data( data.read, package="sirt") dat <- data.read # estimate the Rasch model mod <- sirt::rasch.mml2( dat ) # estimate classification accuracy (3 levels) cutscores <- c( -1, .3 ) # cut scores at theta=-1 and theta=.3 sirt::class.accuracy.rasch( cutscores=cutscores, b=mod$item$b, meantheta=0, sdtheta=mod$sd.trait, theta.l=seq(-4,4,len=200), n.sims=3000) ## Cut Scores ## [1] -1.0 0.3 ## ## WLE reliability (by simulation)=0.671 ## WLE consistency (correlation between two parallel forms)=0.649 ## ## Classification accuracy and consistency ## agree0 agree1 kappa consistency ## analytical 0.68 0.990 0.492 NA ## simulated 0.70 0.997 0.489 0.599 ## ## Probability classification table ## Est_Class1 Est_Class2 Est_Class3 ## True_Class1 0.136 0.041 0.001 ## True_Class2 0.081 0.249 0.093 ## True_Class3 0.009 0.095 0.294
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.