bairt (version 0.1.2)

continue.mcmc.bairt: Continue MCMC for the Estimation of the Two-Parameter or Three-Parameter Normal Ogive Model

Description

This is a function for bairt objects. You can use continue.mcmc for continue the MCMC the Two-Parameter or Three-Parameter normal ogive item response model.

Usage

# S3 method for bairt
continue.mcmc(mcmclist, initial.value = NULL,
  c.prior = NULL, iter = NULL, burning = NULL, thin = NULL,
  parts = NULL, ...)

Arguments

mcmclist

A bairt class object (mcmc.2pnob or mcmc.3pnob).

initial.value

List with initial values.

c.prior

A two dimensional vector which defines the beta prior distribution of guessing parameters. The default is a non-informative prior, Beta(1,1).

iter

Total number of iterations.

burning

Number of burnin iterations.

thin

The thinning interval between consecutive observations.

parts

Number of splits for MCMC chain.

...

Further arguments.

Value

An mcmc.2pnob or mcmc.3pnob object.

Details

If any argument (final.values, c.prior, iter, burning, thin or parts) is NULL, continue.mcmc take the value of the mcmclist.

References

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

A.A. Beguin, A, A & Glas, C.A.W. (2001). MCMC Estimation and Some Model-Fit Analysis of Multidimensional IRT Models. Psychometrika, 66, 541-562.

See Also

mcmc.2pnob and mcmc.3pnob.

Examples

# NOT RUN {
# 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 = 100, burning = 0)

# continue the  MCMC for the Two-Parameter Normal Ogive Model
model21 <- continue.mcmc(model2, iter = 100, burning = 0)

# }
# NOT RUN {
# 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)

#continue the  MCMC for the Three-Parameter Normal Ogive Model
# form 1
initialValues2 <- final.values.mcmc(modelAll3)
modelAll31 <- mcmc.3pnob(MathTest, initial.value = initialValues2,
                     iter = 2000, burning = 0, c.prior = cprior)
# form 2
modelAll32 <- continue.mcmc(modelAll3, iter = 2000, burning = 0)
# }
# NOT RUN {
## End(Not run)


# }