Estimate the Deterministic Input, Noisy And Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi: 10.3102/1076998615595403>.
You can install dina
from CRAN using:
install.packages("dina")
Or, you can be on the cutting-edge development version on GitHub using:
if(!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("tmsalab/dina")
To use the dina
package, load it into R using:
library("dina")
From there, the DINA CDM can be estimated using:
dina_model = dina(<data>, <q>, chain_length = 10000)
To simulate item data under DINA, use:
# Set a seed for reproducibility
set.seed(888)
# Setup Parameters
N = 15 # Number of Examinees / Subjects
J = 10 # Number of Items
K = 2 # Number of Skills / Attributes
# Assign slipping and guessing values for each item
ss = gs = rep(.2, J)
# Simulate identifiable Q matrix
Q = sim_q_matrix(J, K)
# Simulate subject attributes
subject_alphas = sim_subject_attributes(N, K)
# Item data
items_dina = sim_dina_items(subject_alphas, Q, ss, gs)
Steven Andrew Culpepper and James Joseph Balamuta
To ensure future development of the package, please cite dina
package
if used during an analysis or simulations. Citation information for the
package may be acquired by using in R:
citation("dina")
GPL (>= 2)