measr

measr: Bayesian psychometric measurement using Stan - Published in JOSS (2023)

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Keywords

bayesian cdm cmdstanr cognitive-diagnosis cognitive-diagnostic-models dcm diagnostic-classification-models psychometrics r r-package rstan rstats stan

Last synced: 4 months ago · JSON representation ·

Repository

R package for the Bayesian estimation of diagnostic classification models using Stan

Basic Info

Host: GitHub
Owner: wjakethompson
License: gpl-3.0
Language: R
Default Branch: main
Homepage: https://measr.info
Size: 197 MB

Statistics

Stars: 11
Watchers: 3
Forks: 5
Open Issues: 13
Releases: 4

Topics

bayesian cdm cmdstanr cognitive-diagnosis cognitive-diagnostic-models dcm diagnostic-classification-models psychometrics r r-package rstan rstats stan

Created over 4 years ago · Last pushed 5 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# measr 


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Diagnostic classification models (DCMs) are a class of psychometric models that estimate respondent abilities as a profile of proficiency on a pre-defined set of skills, or attributes.
Despite the utility of DCMs for providing fine-grained and actionable feedback with shorter assessments, they have are not widely used in applied settings, in part due to a lack of user-friendly software.
Using [R](https://www.r-project.org/) and [Stan](https://mc-stan.org/), measr (said: "measure") simplifies the process of estimating and evaluating DCMs.
Users can specify different DCM subtypes, define prior distributions, and estimate the model using the [rstan](https://mc-stan.org/rstan/) or [cmdstanr](https://mc-stan.org/cmdstanr/) interface to Stan.
You can then easily examine model parameters, calculate model fit metrics, compare competing models, and evaluate the reliability of the attributes.

## Installation

You can install the released version of measr from [CRAN](https://cran.r-project.org/) with:

```r
install.packages("measr")
```

To install the development version of measr from [GitHub](https://github.com/wjakethompson/measr) use:

```r
# install.packages("remotes")
remotes::install_github("wjakethompson/measr")
```

Because measr is based on Stan, a C++ compiler is required.
For Windows, the [Rtools program](https://cran.r-project.org/bin/windows/Rtools/) comes with a C++ compiler.
On Mac, it's recommended that you install Xcode.
For additional instructions and help setting up the compilers, see the [RStan installation help page](https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started).

## Usage

We can define a DCM using `dcm_specify()`.
This function requires a Q-matrix defining which attributes are measured by each item.
We also identify any item identifier columns.
Other arguments can be specified to customize the type of model to estimate (e.g., type of measurement or structural model; see `?dcmstan::dcm_specify()`).
We can then estimate our specified DCM using `dcm_estimate()`.
We supply our specification and our data set, along with any respondent identifiers.
As with `dcm_specify()`, other arguments can be specified to customize the model estimation process (e.g., estimation backend and method; see `?dcm_estimate()`).

To demonstrate measr's functionality, example data sets are available in the [dcmdata](https://dcmdata.r-dcm.org) package.
Here we use the Examination of Certificate of Proficiency in English (ECPE; [Templin & Hoffman, 2013](https://doi.org/10.1111/emip.12010)) data (see `?dcmdata::ecpe` for details).
Note that by default, measr uses a full Markov chain Monte Carlo (MCMC) estimation with Stan, which can be time and computationally intensive.
For a quicker estimation, we could use Stan's optimizer instead of MCMC by adding `method = "optim"` to the function call.
However, please note that some functionality will be lost when using the optimizer (e.g., the calculation of some model fit criteria requires the use of MCMC).

```{r est-model, eval = FALSE}
library(measr)

model_spec <- dcm_specify(dcmdata::ecpe_qmatrix, identifier = "item_id")

model <- dcm_estimate(dcm_spec = model_spec,
                      data = dcmdata::ecpe_data, identifier = "resp_id",
                      iter = 1000, warmup = 200, chains = 2, cores = 2)
```

Once a model has been estimated, we can then add and evaluate model fit.
This can done through absolute model fit, relative model fit (information criteria), or reliability indices.
Model parameters, respondent classifications, and results of the model fit analyses can then be extracted using `measr_extract()`.

```{r evl-model, eval = FALSE}
model <- add_fit(model, method = "m2")
model <- add_criterion(model, criterion = "loo")
model <- add_reliability(model)

measr_extract(model, "m2")
#> # A tibble: 1 × 3
#>      m2    df     pval
#>        
#> 1  514.   325 1.17e-10
```


---

Contributions are welcome.
To ensure a smooth process, please review the [Contributing Guide](https://measr.info/dev/CONTRIBUTING.html).
Please note that the measr project is released with a [Contributor Code of Conduct](https://measr.info/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

Owner

Name: Jake Thompson
Login: wjakethompson
Kind: user
Location: Lawrence, KS
Company: @atlas-aai

Website: https://wjakethompson.com
Twitter: wjakethompson
Repositories: 6
Profile: https://github.com/wjakethompson

Assistant Director of Psychometrics @atlas-aai.

JOSS Publication

measr: Bayesian psychometric measurement using Stan

Published

November 06, 2023

DOI

10.21105/joss.05742

Volume 8, Issue 91, Page 5742

Authors

W. Jake Thompson

Accessible, Teaching, Learning, and Assessment Systems, University of Kansas

Editor

Chris Hartgerink

Citation (CITATION.cff)

# -----------------------------------------------------------
# CITATION file created with {cffr} R package, v0.5.0
# See also: https://docs.ropensci.org/cffr/
# -----------------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "measr" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'measr: Bayesian Psychometric Measurement Using ''Stan'''
version: 1.0.0
doi: 10.21105/joss.05742
abstract: 'Estimate diagnostic classification models (also called cognitive diagnostic
  models) with ''Stan''. Diagnostic classification models are confirmatory latent
  class models, as described by Rupp et al. (2010, ISBN: 978-1-60623-527-0). Automatically
  generate ''Stan'' code for the general loglinear cognitive diagnostic diagnostic
  model proposed by Henson et al. (2009) <doi:10.1007/s11336-008-9089-5> and other
  subtypes that introduce additional model constraints. Using the generated ''Stan''
  code, estimate the model evaluate the model''s performance using model fit indices,
  information criteria, and reliability metrics.'
authors:
- family-names: Thompson
  given-names: W. Jake
  email: wjakethompson@gmail.com
  orcid: https://orcid.org/0000-0001-7339-0300
preferred-citation:
  type: article
  title: 'measr: Bayesian psychometric measurement using Stan'
  authors:
  - family-names: Thompson
    given-names: W. Jake
    email: wjakethompson@gmail.com
    orcid: https://orcid.org/0000-0001-7339-0300
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  issue: '91'
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contact:
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  email: wjakethompson@gmail.com
  orcid: https://orcid.org/0000-0001-7339-0300
keywords:
- bayesian
- cdm
- cmdstanr
- cognitive-diagnosis
- cognitive-diagnostic-models
- dcm
- diagnostic-classification-models
- psychometrics
- r
- r-package
- rstan
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  title: 'R: A Language and Environment for Statistical Computing'
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  url: https://www.R-project.org/
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  year: '2024'
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    name: R Foundation for Statistical Computing
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- type: software
  title: dcm2
  abstract: 'dcm2: Calculating the M2 Model Fit Statistic for Diagnostic Classification
    Models'
  notes: Imports
  url: https://github.com/atlas-aai/dcm2
  repository: https://CRAN.R-project.org/package=dcm2
  authors:
  - family-names: Hoover
    given-names: Jeffrey
    email: jeffrey.c.hoover@gmail.com
    orcid: https://orcid.org/0000-0002-0276-0308
  - family-names: Thompson
    given-names: W. Jake
    email: wjakethompson@gmail.com
    orcid: https://orcid.org/0000-0001-7339-0300
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  abstract: 'psych: Procedures for Psychological, Psychometric, and Personality Research'
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    given-names: William
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  url: https://www.rcpp.org
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  authors:
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    given-names: Lionel
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  abstract: 'rstan: R Interface to Stan'
  notes: Imports
  url: https://mc-stan.org/rstan/
  repository: https://CRAN.R-project.org/package=rstan
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    given-names: Jiqiang
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    given-names: Jonah
    email: jsg2201@columbia.edu
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  url: https://mc-stan.org/rstantools/
  repository: https://CRAN.R-project.org/package=rstantools
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  - family-names: Gabry
    given-names: Jonah
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    given-names: Andrew
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  notes: Imports
  authors:
  - name: R Core Team
  location:
    name: Vienna, Austria
  year: '2024'
  institution:
    name: R Foundation for Statistical Computing
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  abstract: 'tibble: Simple Data Frames'
  notes: Imports
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  repository: https://CRAN.R-project.org/package=tibble
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  abstract: 'tidyr: Tidy Messy Data'
  notes: Imports
  url: https://tidyr.tidyverse.org
  repository: https://CRAN.R-project.org/package=tidyr
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  - family-names: Wickham
    given-names: Hadley
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  abstract: 'BH: Boost C++ Header Files'
  notes: LinkingTo
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    given-names: Dirk
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  abstract: 'RcppEigen: ''Rcpp'' Integration for the ''Eigen'' Templated Linear Algebra
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  notes: LinkingTo
  url: https://dirk.eddelbuettel.com/code/rcpp.eigen.html
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    given-names: Yuanjun
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  notes: Suggests
  url: https://cli.r-lib.org
  repository: https://CRAN.R-project.org/package=cli
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    given-names: Gábor
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  year: '2024'
- type: software
  title: cmdstanr
  abstract: 'cmdstanr: R Interface to ''CmdStan'''
  notes: Suggests
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    given-names: Jonah
    email: jsg2201@columbia.edu
  - family-names: Češnovar
    given-names: Rok
    email: rok.cesnovar@fri.uni-lj.si
  - family-names: Johnson
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  url: https://github.com/r-lib/crayon#readme
  repository: https://CRAN.R-project.org/package=crayon
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  - family-names: Csárdi
    given-names: Gábor
    email: csardi.gabor@gmail.com
  year: '2024'
- type: software
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  abstract: 'knitr: A General-Purpose Package for Dynamic Report Generation in R'
  notes: Suggests
  url: https://yihui.org/knitr/
  repository: https://CRAN.R-project.org/package=knitr
  authors:
  - family-names: Xie
    given-names: Yihui
    email: xie@yihui.name
    orcid: https://orcid.org/0000-0003-0645-5666
  year: '2024'
- type: software
  title: rmarkdown
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  notes: Suggests
  url: https://pkgs.rstudio.com/rmarkdown/
  repository: https://CRAN.R-project.org/package=rmarkdown
  authors:
  - family-names: Allaire
    given-names: JJ
    email: jj@posit.co
  - family-names: Xie
    given-names: Yihui
    email: xie@yihui.name
    orcid: https://orcid.org/0000-0003-0645-5666
  - family-names: Dervieux
    given-names: Christophe
    email: cderv@posit.co
    orcid: https://orcid.org/0000-0003-4474-2498
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  - family-names: Ushey
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    email: kevin@posit.co
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    email: aron@posit.co
  - family-names: Wickham
    given-names: Hadley
    email: hadley@posit.co
  - family-names: Cheng
    given-names: Joe
    email: joe@posit.co
  - family-names: Chang
    given-names: Winston
    email: winston@posit.co
  - family-names: Iannone
    given-names: Richard
    email: rich@posit.co
    orcid: https://orcid.org/0000-0003-3925-190X
  year: '2024'
- type: software
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  abstract: 'roxygen2: In-Line Documentation for R'
  notes: Suggests
  url: https://roxygen2.r-lib.org/
  repository: https://CRAN.R-project.org/package=roxygen2
  authors:
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    given-names: Hadley
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    orcid: https://orcid.org/0000-0003-4757-117X
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    email: pcd@roxygen.org
  - family-names: Csárdi
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    given-names: Manuel
  year: '2024'
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  title: spelling
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  authors:
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  version: '>= 3.0.0'

GitHub Events

Total

Issues event: 4
Watch event: 2
Delete event: 4
Issue comment event: 12
Push event: 31
Pull request review comment event: 30
Pull request review event: 9
Pull request event: 17
Fork event: 2
Create event: 2

Last Year

Issues event: 4
Watch event: 2
Delete event: 4
Issue comment event: 12
Push event: 31
Pull request review comment event: 30
Pull request review event: 9
Pull request event: 17
Fork event: 2
Create event: 2

Committers

Last synced: 5 months ago

All Time

Total Commits: 689
Total Committers: 6
Avg Commits per committer: 114.833
Development Distribution Score (DDS): 0.068

Past Year

Commits: 133
Committers: 4
Avg Commits per committer: 33.25
Development Distribution Score (DDS): 0.323

Top Committers

Name	Email	Commits
Jake Thompson	w**n@g**m	642
JeffreyCHoover	j**r@g**m	36
auburnjimenez34	a**4@g**m	5
dgkf	1****f	2
Andrew Johnson	a**n@a**m	2
Jones	n**1@h**u	2

Committer Domains (Top 20 + Academic)

home.ku.edu: 1 arjohnsonau.com: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 27
Total pull requests: 52
Average time to close issues: 5 months
Average time to close pull requests: 22 days
Total issue authors: 4
Total pull request authors: 6
Average comments per issue: 0.37
Average comments per pull request: 0.73
Merged pull requests: 35
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 3
Pull requests: 26
Average time to close issues: N/A
Average time to close pull requests: 20 days
Issue authors: 2
Pull request authors: 4
Average comments per issue: 0.0
Average comments per pull request: 0.73
Merged pull requests: 10
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

wjakethompson (23)
ralmond (2)
jrachaelahn (1)
seandamiandevine (1)

Pull Request Authors

wjakethompson (30)
JeffreyCHoover (15)
auburnjimenez34 (4)
andrjohns (1)
dgkf (1)
JonesnatebKU (1)

Top Labels

Issue Labels

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- cran 659 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 3
Total maintainers: 1

cran.r-project.org: measr

Bayesian Psychometric Measurement Using 'Stan'

Homepage: https://measr.info
Documentation: http://cran.r-project.org/web/packages/measr/measr.pdf
License: GPL (≥ 3)
Latest release: 1.0.0
published almost 2 years ago

Versions: 3
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 659 Last month

Rankings

Forks count: 21.9%

Stargazers count: 26.2%

Dependent packages count: 29.8%

Dependent repos count: 35.4%

Average: 40.6%

Downloads: 89.7%

Maintainers (1)

wjakethompson@gmail.com

Last synced: 4 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions

actions/checkout v3 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/lint.yaml actions

actions/checkout v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pkgdown.yaml actions

JamesIves/github-pages-deploy-action v4.4.1 composite
actions/checkout v3 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pr-commands.yaml actions

actions/checkout v3 composite
r-lib/actions/pr-fetch v2 composite
r-lib/actions/pr-push v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/test-coverage.yaml actions

actions/checkout v3 composite
actions/upload-artifact v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

DESCRIPTION cran

R >= 4.1.0 depends
Rcpp >= 0.12.0 imports
RcppParallel >= 5.0.1 imports
dcm2 * imports
dplyr >= 1.1.1 imports
fs * imports
glue * imports
loo * imports
magrittr * imports
methods * imports
posterior * imports
psych * imports
rlang >= 0.4.11 imports
rstan >= 2.26.0 imports
rstantools >= 2.3.0 imports
stats * imports
tibble * imports
tidyr >= 1.3.0 imports
cli * suggests
cmdstanr >= 0.4.0 suggests
crayon * suggests
knitr * suggests
rmarkdown * suggests
roxygen2 * suggests
spelling * suggests
testthat >= 3.0.0 suggests

.github/workflows/update-citation-cff.yaml actions

actions/checkout v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

measr

Science Score: 100.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.Rmd

Owner

JOSS Publication

measr: Bayesian psychometric measurement using Stan

Authors

Editor

Tags

Citation (CITATION.cff)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

cran.r-project.org: measr

Rankings

Maintainers (1)

Dependencies