gofIRT {eRm} | R Documentation |
This function computes various model tests and fit indices for objects of class ppar
: Collapsed deviance, Casewise deviance, Rost's LR-test, Hosmer-Lemeshow test, R-Squared measures, confusion matrix, ROC analysis.
## S3 method for class 'ppar'
gofIRT(object, groups.hl = 10, cutpoint = 0.5)
object |
Object of class |
groups.hl |
Number of groups for Hosmer-Lemeshow test (see details). |
cutpoint |
Integer between 0 and 1 for computing the 0-1 model matrix from the estimated probabilities |
So far this test statistics are implemented only for dichotomous models without NA's. The Hosmer-Lemeshow test is computed by splitting the response vector into percentiles, e.g. groups.hl = 10
corresponds to decile splitting.
The function gofIRT
returns an object of class gof
containing:
test.table |
Ouput for model tests. |
R2 |
List with R-squared measures. |
classifier |
Confusion matrix, accuracy, sensitivity, specificity. |
AUC |
Area under ROC curve. |
Gini |
Gini coefficient. |
ROC |
FPR and TPR for different cutpoints. |
opt.cut |
Optimal cutpoint determined by ROC analysis. |
predobj |
Prediction output from ROC analysis ( |
Mair, P., Reise, S. P., and Bentler, P. M. (2008). IRT goodness-of-fit using approaches from logistic regression. UCLA Statistics Preprint Series.
itemfit.ppar
,personfit.ppar
,LRtest
#Goodness-of-fit for a Rasch model
res <- RM(raschdat1)
pres <- person.parameter(res)
gof.res <- gofIRT(pres)
gof.res
summary(gof.res)