Estimating Parameters with IRTpp
In IRTpp: Estimating IRT Parameters using the IRT Methodology

Estimating Item Parameters according to a IRT model with the IRTpp package

The main purpose of the irtpp package is to estimate item parameters according to a IRT model, to begin the paremeter estimation for a test, use the function irtpp

library(IRTpp)
tst = simulateTest(model="3PL")

## Calibrate this test with a 2PL model.
est = irtpp(tst$test,"1PL")

Now est holds the return of the estimation procedure

names(est)
est$z
est$LL

in est$z there is a named list of the IRT parameters calibrated for this test. It is also easy to visualize all the Item Caracteristic Curves (ICC) of the test, with the function test.plot, this is a visual resume of the parameters.

test.plot(est$z)

Alternatively , irtpp offers other options such as displaying loglikelihood based statistics , reading from files or changing the initial values of the estimation procedure (for advanced uses).

## Calibrating the same test under a 3PL model and displaying the AIC and BIC statistics
est = irtpp(tst$test,"3PL", loglikflag=T)

The item caracteristic curve of all the items of the test can be drawn to compare between IRT models.

test.plot(est$z)

Or for an specific item:

test.plot(est$z,2)

Estimating latent traits of the individuals

IRTpp package also supports estimating latent traits of individuals according to IRT methodologies. User the function individual.traits to estimate the individual latent traits for a test.

zz = parameter.matrix(est$z,byrow = F)
th = individual.traits(model="3PL", itempars = zz,method = "EAP",dataset = tst$test, probability_matrix = est$prob_mat)

##The latent traits.
hist(th[,ncol(th)],breaks=40)