chain.study.bairt: Convergence graphs for the simulated values
In bairt: Bayesian Analysis of Item Response Theory Models

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

Convergence graphs for the study of the simulated values for an MCMC marginal chain.

1
2
3

## S3 method for class 'bairt'
chain.study(mcmclist, parameter = "a", chain = 1,
  line = TRUE, ...)

`mcmclist`	A mcmc.2pnob or mcmc.3pnob class object.
`parameter`	The parameter (a, b, c or theta) for graphing.
`chain`	The number of the chain that will be graphed.
`line`	A red line that represent the posterior mean of the simulated values.
`...`	Further arguments.

The top left graph displays the sequence of simulated values and the top right graph displays the lagged correlations of the sequence as a function of the lag value. The bottom left graph is an histogram of the simulated values and the bottom right graph is the box plot of the simulated values.

Convergence graphs for the study of the simulated values for an MCMC marginal chain.

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.

# 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)
chain.study(model2, parameter = "b", chain = 12)
chain.study(model2, parameter = "theta", chain = 10)


# For all examinees of the data MathTest
# Two-Parameter Normal Ogive Model
modelAll2 <- mcmc.2pnob(MathTest, iter = 3500, burning = 500, thin = 10)
check.plot(modelAll2)
chain.study(modelAll2, parameter = "b", chain = 14)
chain.study(modelAll2, parameter = "theta", chain = 10)

# Three-Parameter Normal Ogive Model
modelAll3 <- mcmc.3pnob(MathTest, iter = 3500, burning = 500, thin = 10)
check.plot(modelAll3)
chain.study(modelAll3, parameter = "b", chain = 12)
chain.study(modelAll3, parameter = "c", chain = 10)


## End(Not run)