https://github.com/tmsalab/rrum
The goal of rrum is to provide an implementation of Gibbs sampling algorithm for Bayesian Estimation of reduced Reparametrized Unifed Model (rRUM), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.
https://github.com/tmsalab/rrum
armadillo cdm cognitive-diagnostic-models gibbs-sampling-algorithm psychometrics r rcpparmadillo rrum rstats
Last synced: 11 months ago
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The goal of rrum is to provide an implementation of Gibbs sampling algorithm for Bayesian Estimation of reduced Reparametrized Unifed Model (rRUM), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.
- Host: GitHub
- URL: https://github.com/tmsalab/rrum
- Owner: tmsalab
- Created: 2017-09-29T04:36:56.000Z (over 8 years ago)
- Default Branch: main
- Last Pushed: 2023-11-29T08:04:56.000Z (about 2 years ago)
- Last Synced: 2025-03-10T13:49:13.909Z (12 months ago)
- Topics: armadillo, cdm, cognitive-diagnostic-models, gibbs-sampling-algorithm, psychometrics, r, rcpparmadillo, rrum, rstats
- Language: C++
- Homepage: https://tmsalab.github.io/rrum
- Size: 145 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# rrum
[](https://github.com/tmsalab/rrum/actions/workflows/R-CMD-check.yaml)
[-brightgreen.svg?style=flat)](https://www.gnu.org/licenses/gpl-2.0.html)
[](https://cran.r-project.org/package=rrum)
[](https://cran.r-project.org/web/checks/check_results_rrum.html)
[](https://www.r-pkg.org/pkg/rrum)
[](https://www.r-pkg.org/pkg/rrum)
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) .
## Installation
You can install `rrum` from CRAN using:
```{r}
#| label: cran-installation
#| eval: false
install.packages("rrum")
```
Or, you can be on the cutting-edge development version on GitHub using:
```{r}
#| label: gh-installation
#| eval: false
# install.packages('remotes')
remotes::install_github("tmsalab/rrum")
```
## Usage
To use `rrum`, load the package using:
```{r}
#| label: example
#| eval: false
library("rrum")
```
From here, the rRUM model can be estimated using:
```{r}
#| label: rrum-est
#| eval: false
rrum_model = rrum(, )
```
Additional parameters can be accessed with:
```{r}
#| label: rrum-est-adv
#| eval: false
rrum_model = rrum(, , chain_length = 10000L,
as = 1, bs = 1, ag = 1, bg = 1,
delta0 = rep(1, 2^ncol(Q)))
```
`rRUM` item data can be simulated using:
```{r}
#| label: rrum-sim
#| eval: false
# 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
# Simulate identifiable Q matrix
Q = sim_q_matrix(J, K)
# Penalties for failing to have each of the required attributes
rstar = .5 * Q
# The probabilities of answering each item correctly for individuals
# who do not lack any required attribute
pistar = rep(.9, J)
# Latent Class Probabilities
pis = 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 items
rrum_items = simcdm::sim_rrum_items(Q, rstar, pistar, subject_alphas)
```
## Authors
Steven Andrew Culpepper, Aaron Hudson, and James Joseph Balamuta
## Citing the `rrum` package
To 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*:
```{r}
#| label: citation
#| eval: false
citation("rrum")
```
## License
GPL (>= 2)