[REVIEW]: ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization

[editorialbot]

Submitting author: @limengbinggz (Mengbing Li)
Repository: https://github.com/limengbinggz/ddtlcm
Branch with paper.md (empty if default branch): main
Version: v0.2.1
Editor: @Nikoleta-v3
Reviewers: @jamesuanhoro, @larryshamalama
Archive: 10.5281/zenodo.12711232

Status

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Markdown: [![status](https://joss.theoj.org/papers/2cffa48f57384769d086069f824fd020/status.svg)](https://joss.theoj.org/papers/2cffa48f57384769d086069f824fd020)

Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@jamesuanhoro & @larryshamalama, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
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✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @larryshamalama

📝 Checklist for @jamesuanhoro

[editorialbot]

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.03 s (1033.3 files/s, 170689.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               24            322           1377           1629
XML                              1              0            184           1513
Markdown                         5             96              0            259
TeX                              2              8              0            105
Rmd                              2            120            160            102
YAML                             2             11              6             55
-------------------------------------------------------------------------------
SUM:                            36            557           1727           3663
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1596

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v061.i13 is OK
- 10.18637/jss.v042.i10 is OK
- 10.1109/TPAMI.2014.2313115 is OK
- 10.1080/03610918.2012.718840 is OK

MISSING DOIs

- 10.1093/oso/9780198526155.003.0042 may be a valid DOI for title: Density modeling and clustering using Dirichlet diffusion trees

INVALID DOIs

- None

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[Nikoleta-v3]

Hey @jamesuanhoro, @larryshamalama this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step is to create a checklist for your review by entering

@editorialbot generate my checklist

as the top of a new comment in this thread.

These checklists contain the JOSS requirements ✅ As you go over the submission, please check any items that you feel have been satisfied. The first comment in this thread also contains links to the JOSS reviewer guidelines.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention #6220 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please let me know if any of you require some more time. We can also use EditorialBot (our bot) to set automatic reminders if you know you'll be away for a known period of time.

Please feel free to ping me (@Nikoleta-v3) if you have any questions/concerns. 😄 🙋🏻

[Nikoleta-v3]

@limengbinggz, could you please add the DOI for one of your references? See: #6220 (comment)

[larryshamalama]

Review checklist for @larryshamalama

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the https://github.com/limengbinggz/ddtlcm?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@limengbinggz) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[larryshamalama]

Hi @limengbinggz, great software and great method! From one fellow biostats PhD to another, congratulations on your hard work :)

Below are my questions/comments, on top of some other quick things that I am opening as issue(s)/PR(s) in your repo

1. Weak Separation and State of the Field

State of the field: Do the authors describe how this software compares to other commonly-used packages?

It took me a while to understand what is meant by "weak separation", which is the focal point of this work. Perhaps this is because I am not so familiar with Bayesian tree-based methods... I was initially not sure if using other software that you mentioned (e.g. poLCA, BayesLCA, randomLCA) would yield worse results on your simulated data but Figure 3 in your methods paper seems to confirm this. I am thinking that it would be beneficial to clarify this result here since it would motivate further why we should use your package and not the other ones. What do you think?

Minor comment: lines 21, 22: "classes that share proximity to one another in the tree are shrunk towards ancestral classes a priori" Do you think that you can massage this a bit? I'm not sure if I fully understand, but this sentence seems importance since it highlights on a higher level what this method is doing under the food (re: summary bullet point above).

2. 50 burn-in, 100 posterior draws

In your example, you seem to use 50 burn-in draws and 100 posterior draws. Is that sufficient? As a user, how would I know when the MCMC converges with your software? If I am thinking of conventional MCMC-ing, these seem like low numbers, especially that, in your example, you use $N = 496$ which is larger than the total number of draws. In section 5.1 of your methods paper, you seem to use much more draws in the Gibbs sampler (7,000 and 12,000).

3. Singleton node warnings

I am getting many In checkTree(object) : Tree contains singleton nodes. when running your quickstart. I imagine that this means that, for a specific category, there is only one member, which can happen, but just wanted to double check that this can be normal/okay. Can you briefly comment on this?

[jamesuanhoro]

Review checklist for @jamesuanhoro

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the https://github.com/limengbinggz/ddtlcm?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@limengbinggz) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

Additional notes

Hello @limengbinggz:

• First, this is extensive work :)
• I have created some issues, I am open to discussion about them
• I have also made some pull requests re minor suggestions for the code
• I tried to reference the issues and PR below.
• I also noticed the warnings @larryshamalama noted.

[Nikoleta-v3]

Hey @limengbinggz 👋🏻 did you get a chance to look over the comments/issues that the reviewers raised? 😄

[Nikoleta-v3]

👋🏻 @limengbinggz

[limengbinggz]

👋🏻 @limengbinggz

Thank for for checking in. We are working on incorporating the reviewers' comments into the revision, and will push to the repo when we are ready. Thanks for waiting.

[Nikoleta-v3]

Thank you for the update!

[limengbinggz]

@limengbinggz, could you please add the DOI for one of your references? See: #6220 (comment)

Thank you for pointing out. We have added the DOI for the reference. The paper is updated in commit
4f9a157

[limengbinggz]

@editorialbot generate pdf

[Nikoleta-v3]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v061.i13 is OK
- 10.18637/jss.v042.i10 is OK
- 10.1109/TPAMI.2014.2313115 is OK
- 10.1093/oso/9780198526155.003.0042 is OK
- 10.1080/03610918.2012.718840 is OK

MISSING DOIs

- No DOI given, and none found for title: randomLCA: An R package for latent class with rand...
- No DOI given, and none found for title: Tree-Regularized Bayesian Latent Class Analysis fo...
- No DOI given, and none found for title: Validating Bayesian inference algorithms with simu...

INVALID DOIs

- None

[Nikoleta-v3]

@limengbinggz can you check if you can find DOIs for the above publications? ⬆️

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[limengbinggz]

I appreciate your advice on the vignettes. Could you please give me more specific suggestions about what can be added to the vignettes for improvement? Thank you!

The current vignette is really to accompany your paper. I was thinking of having vignettes for the different functionalities of the package. Are all the functionalities of ddtlcm being captured by the current vignette?

Thanks! I do think the current vignettes is to demonstrate all the functionalities of the package, basically data simulation, model estimation and inference, and visualization.

[limengbinggz]

@limengbinggz can you check if you can find DOIs for the above publications? ⬆️

I have updated the DOI for randomLCM. The other two references do not have DOIs so I am leaving them blank. Thanks!

[Nikoleta-v3]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v061.i13 is OK
- 10.18637/jss.v042.i10 is OK
- 10.18637/jss.v081.i13 is OK
- 10.1109/TPAMI.2014.2313115 is OK
- 10.1093/oso/9780198526155.003.0042 is OK
- 10.1080/03610918.2012.718840 is OK

MISSING DOIs

- No DOI given, and none found for title: Tree-Regularized Bayesian Latent Class Analysis fo...
- No DOI given, and none found for title: Validating Bayesian inference algorithms with simu...

INVALID DOIs

- None

[Nikoleta-v3]

Post-Review Checklist for Editor and Authors

Additional Author Tasks After Review is Complete

• Double check authors and affiliations (including ORCIDs)
• Make a release of the software with the latest changes from the review and post the version number here. This is the version that will be used in the JOSS paper.
• Archive the release on Zenodo/figshare/etc and post the DOI here.
• Make sure that the title and author list (including ORCIDs) in the archive match those in the JOSS paper.
• Make sure that the license listed for the archive is the same as the software license.

Editor Tasks Prior to Acceptance

• Read the text of the paper and offer comments/corrections (as either a list or a pull request)
• Check that the archive title, author list, version tag, and the license are correct
• Set archive DOI with @editorialbot set <DOI here> as archive
• Set version with @editorialbot set <version here> as version
• Double check rendering of paper with @editorialbot generate pdf
• Specifically check the references with @editorialbot check references and ask author(s) to update as needed
• Recommend acceptance with @editorialbot recommend-accept

[Nikoleta-v3]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.18637/jss.v061.i13 is OK
- 10.18637/jss.v042.i10 is OK
- 10.18637/jss.v081.i13 is OK
- 10.1109/TPAMI.2014.2313115 is OK
- 10.1093/oso/9780198526155.003.0042 is OK
- 10.1080/03610918.2012.718840 is OK

MISSING DOIs

- No DOI given, and none found for title: Tree-Regularized Bayesian Latent Class Analysis fo...
- No DOI given, and none found for title: Validating Bayesian inference algorithms with simu...

INVALID DOIs

- None

[editorialbot]

👋 @openjournals/dsais-eics, this paper is ready to be accepted and published.

Check final proof 👉📄 Download article

If the paper PDF and the deposit XML files look good in openjournals/joss-papers#5620, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

[crvernon]

🔍 checking out the following:

• reviewer checklists are completed or addressed
• version set
• archive set
• archive names (including order) and title in archive matches those specified in the paper
• archive uses the same license as the repo and is OSI approved as open source
• archive DOI and version match or redirect to those set by editor in review thread
• paper is error free - grammar and typos
• paper is error free - test links in the paper and bib
• paper is error free - refs preserve capitalization where necessary
• paper is error free - no invalid refs without justification

[crvernon]

@editorialbot generate pdf

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[crvernon]

👋 @limengbinggz - Thanks for your work on this. We just need to clear one more thing before I can accept this for publication:

• The license listed in your Zenodo archive should match the license listed for your software. Please edit the metadata of your Zenodo archive to make this so. No need to conduct a new release.

Let me know when this as done and we will move forward. Thanks!

[limengbinggz]

https://github.com/limengbinggz/ddtlcm

👋 @limengbinggz - Thanks for your work on this. We just need to clear one more thing before I can accept this for publication:

• The license listed in your Zenodo archive should match the license listed for your software. Please edit the metadata of your Zenodo archive to make this so. No need to conduct a new release.

Let me know when this as done and we will move forward. Thanks!

Thank you for the nudge! I have corrected my license on Zenodo.

[crvernon]

@editorialbot accept

[editorialbot]

Doing it live! Attempting automated processing of paper acceptance...

[editorialbot]

Ensure proper citation by uploading a plain text CITATION.cff file to the default branch of your repository.

If using GitHub, a Cite this repository menu will appear in the About section, containing both APA and BibTeX formats. When exported to Zotero using a browser plugin, Zotero will automatically create an entry using the information contained in the .cff file.

You can copy the contents for your CITATION.cff file here:

CITATION.cff

cff-version: "1.2.0"
authors:
- family-names: Li
  given-names: Mengbing
  orcid: "https://orcid.org/0000-0002-2264-8006"
- family-names: Wu
  given-names: Bolin
- family-names: Stephenson
  given-names: Briana
- family-names: Wu
  given-names: Zhenke
  orcid: "https://orcid.org/0000-0001-7582-669X"
contact:
- family-names: Li
  given-names: Mengbing
  orcid: "https://orcid.org/0000-0002-2264-8006"
- family-names: Wu
  given-names: Zhenke
  orcid: "https://orcid.org/0000-0001-7582-669X"
doi: 10.5281/zenodo.12711232
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Li
    given-names: Mengbing
    orcid: "https://orcid.org/0000-0002-2264-8006"
  - family-names: Wu
    given-names: Bolin
  - family-names: Stephenson
    given-names: Briana
  - family-names: Wu
    given-names: Zhenke
    orcid: "https://orcid.org/0000-0001-7582-669X"
  date-published: 2024-07-15
  doi: 10.21105/joss.06220
  issn: 2475-9066
  issue: 99
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6220
  title: "ddtlcm: An R package for overcoming weak separation in
    Bayesian latent class analysis via tree-regularization"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06220"
  volume: 9
title: "ddtlcm: An R package for overcoming weak separation in Bayesian
  latent class analysis via tree-regularization"

If the repository is not hosted on GitHub, a .cff file can still be uploaded to set your preferred citation. Users will be able to manually copy and paste the citation.

Find more information on .cff files here and here.

[editorialbot]

🐘🐘🐘 👉 Toot for this paper 👈 🐘🐘🐘

[editorialbot]

🚨🚨🚨 THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! 🚨🚨🚨

Here's what you must now do:

0. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.06220 joss-papers#5624
1. Wait five minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.06220
2. If everything looks good, then close this review issue.
3. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

[crvernon]

🥳 Congratulations on your new publication @limengbinggz! Many thanks to @Nikoleta-v3 for editing and @jamesuanhoro and @larryshamalama for your time, hard work, and expertise!! JOSS wouldn't be able to function nor succeed without your efforts.

Please consider becoming a reviewer for JOSS if you are not already: https://reviewers.joss.theoj.org/join

[editorialbot]

🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉

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</a>

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[limengbinggz]

🥳 Congratulations on your new publication @limengbinggz! Many thanks to @Nikoleta-v3 for editing and @jamesuanhoro and @larryshamalama for your time, hard work, and expertise!! JOSS wouldn't be able to function nor succeed without your efforts.

Please consider becoming a reviewer for JOSS if you are not already: https://reviewers.joss.theoj.org/join

Thank you very much to the editors and reviewers for your time and hard work! I really appreciate you help!