README.md
In dina: Bayesian Estimation of DINA Model

`dina` R package

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

Citing the `dina` package

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: