person.posterior {PCMRS}

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)

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.

Value

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

Author(s)

Gunther Schauberger
[e-mail]
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, https://journals.sagepub.com/doi/10.1177/0146621617748322

See Also

PCMRS PCMRS-package

Examples

## Not run: 
################################################
## 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)

## End(Not run)