qualtdict: Generating Variable Dictionaries and Labelled Data Exports of Qualtrics Surveys

[lyh970817]

Submitting Author Name: Yuhao Lin Submitting Author Github Handle: @lyh970817 Repository: https://github.com/lyh970817/qualtdict Version submitted: 0.0.0.9000 Submission type: Standard Editor: @maurolepore Reviewers: TBD

Archive: TBD Version accepted: TBD Language: en

• Paste the full DESCRIPTION file inside a code block below:

Package: qualtdict
Title: Generating Variable Dictionaries and Labelled Data Exports of Qualtrics
    Surveys
Version: 0.0.0.9000
Authors@R:
    person("Yuhao", "Lin", , "[email protected]", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-6357-5731"))
Description: Provides functions that generate variable dictionaries from
    'Qualtrics' <https://www.qualtrics.com/about/> surveys and labelled
    survey data based on the dictionary. This package is built upon the R
    package 'qualtRics' <https://github.com/ropensci/qualtRics/> which
    provides access to 'Qualtrics' survey data and metadata via the 'Qualtrics' API
    <https://api.qualtrics.com/>.
License: MIT + file LICENSE
URL: https://github.com/lyh970817/qualtdict
BugReports: https://github.com/lyh970817/qualtdict/issues
Imports:
    crul,
    dplyr,
    glue,
    haven,
    magrittr,
    openNLP,
    purrr,
    qualtRics,
    rlang,
    sjlabelled,
    slowraker,
    SnowballC,
    stringi,
    stringr,
    tibble,
    tidyr,
    xml2
Suggests:
    covr,
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    vcr (>= 0.6.0)
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Config/testthat/start-first: dict_generate, dict_validate, get_survey_data
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • [ ] data retrieval
  • [ ] data extraction
  • [x] data munging
  • [ ] data deposition
  • [ ] data validation and testing
  • [ ] workflow automation
  • [ ] version control
  • [ ] citation management and bibliometrics
  • [ ] scientific software wrappers
  • [ ] field and lab reproducibility tools
  • [ ] database software bindings
  • [ ] geospatial data
  • [ ] text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

Qualtrics is an online survey and data collection software platform. While the qualtRics R package implements data retrieval from the Qualtrics platform, this package 'qualtdict' further processes its output to generate variable dictionaries and labelled data designed to be used for data analyses directly.

• Who is the target audience and what are scientific applications of this package?

The target audience is those who use the Qualtrics survey platform to collect data. This package generates variable dictionaries and labelled data designed to be used for data analyses directly.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

No, but there is the similar qualtRics R package that retrieves a broader range of data from Qualtrics than this package utilises. The output formats from qualtRics are much less user-friendly, for example, it retrieves survey metadata in a nested-list, json-like format, while this package rearranges essential parts of this metadata (retrieved using quatRics) into a publishable variable dictionary in a table format that can be visually inspected in, for example, excel.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Yes.

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