View source: R/person.posterior.R
person.posterior | R Documentation |
Calculates posterior estimates for both person parameters, namely the ability parameters theta and the response style parameters gamma.
person.posterior(model, cores = 30, tol = 1e-04, maxEval = 600, which = NULL)
model |
Object of class |
cores |
Number of cores to be used in parallelized computation. |
tol |
The maximum tolerance for numerical integration, default 1e-4.
For more details see |
maxEval |
The maximum number of function evaluations needed in numerical integration.
If specified as 0 implies no limit. For more details see |
which |
Optional vector to specify that only for a subset of all persons the posterior estimate is calculated. |
Matrix containing all estimates of person parameters, both theta and gamma.
Gunther Schauberger
gunther.schauberger@tum.de
https://www.sg.tum.de/epidemiologie/team/schauberger/
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
PCMRS
PCMRS-package
## 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)
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