Implementation of Gibbs sampling algorithm for Bayesian Estimation
of the Reduced Reparameterized Unified Model ('rrum'), described by
Culpepper and Hudson (2017)
The goal of rrum
is to provide an implementation of Gibbs sampling
algorithm for Bayesian Estimation of Reduced Reparameterized Unified
Model (rrum), described by Culpepper and Hudson (2017) <doi:
10.1177/0146621617707511>.
You can install rrum
from CRAN using:
install.packages("rrum")
Or, you can be on the cutting-edge development version on GitHub using:
if(!requireNamespace("devtools")) install.packages("devtools")devtools::install_github("tmsalab/rrum")
To use rrum
, load the package using:
library("rrum")#> Loading required package: simcdm
From here, the rRUM model can be estimated using:
rrum_model = rrum(<data>, <q>)
Additional parameters can be accessed with:
rrum_model = rrum(<data>, <q>, chain_length = 10000L,as = 1, bs = 1, ag = 1, bg = 1,delta0 = rep(1, 2^ncol(Q)))
rRUM
item data can be simulated using:
# Set a seed for reproducibilityset.seed(888)# Setup ParametersN = 15 # Number of Examinees / SubjectsJ = 10 # Number of ItemsK = 2 # Number of Skills / Attributes# Simulate identifiable Q matrixQ = sim_q_matrix(J, K)# Penalties for failing to have each of the required attributesrstar = .5 * Q# The probabilities of answering each item correctly for individuals# who do not lack any required attributepistar = rep(.9, J)# Latent Class Probabilitiespis = c(.1, .2, .3, .4)# Generate latent attribute profile with custom probability (N subjects by K skills)subject_alphas = sim_subject_attributes(N, K, prob = pis)# Simulate rrum itemsrrum_items = simcdm::sim_rrum_items(Q, rstar, pistar, subject_alphas)
Steven Andrew Culpepper, Aaron Hudson, and James Joseph Balamuta
rrum
packageTo ensure future development of the package, please cite rrum
package
if used during an analysis or simulation study. Citation information for
the package may be acquired by using in R:
citation("rrum")
GPL (>= 2)
rRUM_Gibbs()
in favor of rrum()
.pi_reference()
in favor of simcdm::attribute_classes()
.CITATION
file for citing both the APM paper and package.simcdm
README
examples