PCMRS (version 0.1-5)

person.posterior: Calculate Posterior Estimates for Person Parameters

Description

Calculates posterior estimates for both person parameters, namely the ability parameters theta and the response style parameters gamma.

Usage

person.posterior(model, cores = 30, tol = 1e-04, maxEval = 600, which = NULL)

Value

Matrix containing all estimates of person parameters, both theta and gamma.

Arguments

model

Object of class PCMRS.

cores

Number of cores to be used in parallelized computation.

tol

The maximum tolerance for numerical integration, default 1e-4. For more details see adaptIntegrate.

maxEval

The maximum number of function evaluations needed in numerical integration. If specified as 0 implies no limit. For more details see adaptIntegrate.

which

Optional vector to specify that only for a subset of all persons the posterior estimate is calculated.

Author

Gunther Schauberger

https://www.sg.tum.de/epidemiologie/team/schauberger/

References

Tutz, Gerhard, Schauberger, Gunther and Berger, Moritz (2018): Response Styles in the Partial Credit Model, Applied Psychological Measurement, tools:::Rd_expr_doi("10.1177/0146621617748322")

See Also

PCMRS PCMRS-package

Examples

# \dontshow{
k <- 4; n <- 50; I <- 4
set.seed(1860)
Y <- as.data.frame(matrix(sample(1:k, I*n, TRUE),nrow = n))
Y <- data.frame(lapply(Y, as.ordered))

mini.ex <- PCMRS(Y, cores = 2)
mini.ex
# }
if (FALSE) {
################################################
## Small example to illustrate model and person estimation
################################################

data(tenseness)

set.seed(5)
samples <- sample(1:nrow(tenseness), 100)
tense_small <- tenseness[samples,1:4]

m_small <- PCMRS(tense_small, cores = 2)
m_small
plot(m_small)

persons <- person.posterior(m_small, cores = 2)
plot(jitter(persons, 100))

################################################
## Example from Tutz et al. 2017:
################################################

data(emotion)
m.emotion <- PCMRS(emotion)
m.emotion

plot(m.emotion)
}