irc.bairt: Plot of posterior density of the item response curve
In bairt: Bayesian Analysis of Item Response Theory Models

Description Usage Arguments Details Value Author(s) References See Also Examples

Plot of the j-th item response curve.

1
2
3

## S3 method for class 'bairt'
irc(mcmclist, item = 1, color = "red", prob = c(0.05,
  0.95), ...)

`mcmclist`	A mcmc.2pnob or mcmc.3pnob class object.
`item`	The number of j-th item.
`color`	Item response curve color.
`prob`	A vector of length two for defined the percentiles of the posterior density.
`...`	Further arguments.

The solid line corresponds to the location of the posterior mean and the points correspond to the percentiles determined by prob. prob = c(0.05, 0.95) corresponds to the 5th and 95th percentils of the posterior density respectively.

Plot of the j-th item response curve.

Javier Mart<c3><ad>nez

Johnson, V. E. & Albert, J. H. (1999). Ordinal Data Modeling. New York: Springer.

mcmc.2pnob, mcmc.3pnob and continue.mcmc.bairt.

# data for model
data("MathTest")

# Only for the first 500 examinees of the data MathTest
# Two-Parameter Normal Ogive Model
model2 <- mcmc.2pnob(MathTest[1:500,], iter = 400, burning = 100)
check.plot(model2)
irc(model2, item = 3)


# For all examinees of the data MathTest
# Three-Parameter Normal Ogive Model
# selection of the prior for 5 response options
cprior <- select.c.prior(5)
modelAll3 <- mcmc.3pnob(MathTest, iter = 1000, burning = 0,
                    c.prior = cprior)
irc(modelAll3 , item = 1, color = "blue")
irc(modelAll3 , item = 1, color = "blue", prob = c(0.1, 0.9))


## End(Not run)