[REVIEW]: Multivariate Covariance Generalized Linear Models in Python: The mcglm library

[editorialbot]

Submitting author: @jeancmaia (Jean Carlos Maia)
Repository: https://github.com/jeancmaia/mcglm
Branch with paper.md (empty if default branch): main
Version: 0.2.1
Editor: @AJQuinn
Reviewers: @Spaak, @bkrayfield
Archive: Pending

Status

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Markdown: [![status](https://joss.theoj.org/papers/b0cf48e0bc9265d2ad754b1d33475936/status.svg)](https://joss.theoj.org/papers/b0cf48e0bc9265d2ad754b1d33475936)

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

@Spaak & @bkrayfield, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @AJQuinn know.

✨ 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 @bkrayfield

📝 Checklist for @Spaak

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.68 s (319.9 files/s, 27347.6 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          10            584            640           3674
CSS                              4             36             12           1838
R                                1             76             74           1515
Jupyter Notebook                 4              0           7572            836
JavaScript                       6             80             88            633
TeX                              1             38              0            281
Markdown                         2             48              0            222
JSON                           184              0              0            184
YAML                             2              6              4             41
TOML                             1              5              0             25
make                             1              4              7              9
reStructuredText                 1              6              7              7
-------------------------------------------------------------------------------
SUM:                           217            883           8404           9265
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1744

[editorialbot]

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

OK DOIs

- 10.7287/PEERJ.PREPRINTS.1686V1 is OK
- 10.48550/arXiv.1809.10756 is OK
- 10.48550/arXiv.1810.09538 is OK
- 10.18637/jss.v076.i01 is OK
- 10.18637/jss.v084.i04 is OK
- 10.48550/arXiv.1409.7482 is OK
- 10.1111/j.2517-6161.1987.tb01685.x is OK
- 10.1002/1097-0258(20000730)19:14<1952::AID-SIM474>3.0.CO;2-K is OK
- 10.1214/12-EJS721 is OK
- 10.1016/j.jmva.2013.05.001 is OK
- 10.2307/2344614 is OK
- 10.1007/978-3-642-21551-3_24 is OK
- 10.1214/ss/1177013604 is OK
- 10.1214/aos/1176345451 is OK
- 10.1002/9781118445112.stat07536 is OK
- 10.2307/2841583 is OK
- 10.2307/2333849 is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.1038/s41592-019-0686-2 is OK
- 10.18637/jss.v084.i04 is OK
- 10.25080/Majora-92bf1922-011 is OK
- 10.1177/0962280212445834 is OK
- 10.1214/12-EJS721 is OK
- 10.1016/j.jmva.2013.05.001 is OK
- 10.1093/biomet/73.1.13 is OK
- 10.1111/rssc.12145 is OK
- 10.1515/ijb-2017-0001 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[editorialbot]

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

[AJQuinn]

👋🏼 @jeancmaia @Spaak @bkrayfield this is the review thread for the paper. All of our communications will happen here from now on.

For @Spaak and @bkrayfield - 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. Please can you do this soon as a confirmation that you've seen the review starting.

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. Summary conversation is great on this thread but try to avoid substantial discussion about the repository here, this should take place in issues on the source repository.

When discussing the submission on an issue thread, please mention #6037 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 (@AJQuinn) if you have any questions/concerns.

[bkrayfield]

Review checklist for @bkrayfield

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/jeancmaia/mcglm?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@jeancmaia) 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?

[Spaak]

Review checklist for @Spaak

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/jeancmaia/mcglm?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@jeancmaia) 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?

[Spaak]

@jeancmaia As for API docs: some more details could be added. power_fixed/maxiter/tol/tuning/weights are all underspecified. (I can imagine some things they do in the optimization step, but better to make this explicit, e.g. by briefly explaining the type of optimization done here.) Also Ntrial has a capital N (against common style).

[Spaak]

@jeancmaia I appreciate the extensive tutorial (jeancmaia/mcglm#7) but that appears to be the only web presence besides the PyPI install page (and github). I'd recommend at least making sure there is a hosted version of the API docs available somewhere.

Also there are no community guidelines (see review checklist item) anywhere, I'd recommend adding these to either wherever you end up putting the web API docs or (and) simply in README.md on github.

[Spaak]

@jeancmaia I'd recommend going over the paper a final time for a thorough language check. While it's clearly written, there are some minor issues that should be (easy to) fix(ed).

[jeancmaia]

@Spaak Thanks for the comprehensive feedback. I have revamped the project by incorporating all the aforementioned items.

The new API Docs is hosted on: https://mcglm.readthedocs.io/en/latest/
The new paper is available on: https://github.com/jeancmaia/mcglm/blob/main/paper.md

It would be great if you could check the project out again. Thanks :)

[AJQuinn]

Thanks @Spaak for the review and to @jeancmaia for the quick response.

@bkrayfield - thanks for your work so far, do you have a sense when you'd be able to complete the review/checklist? Let me know if you need any additional input.

[jeancmaia]

Hey @AJQuinn, I hope you're doing well. Just to catch up. I wanted to check in to see if there's anything else you need from me to move forward with the article review. Thank you for your time!"

[crvernon]

👋 @jeancmaia - I am the AEiC for this track of submissions and I can help out a bit here. I looks like there are still a few open pull requests. Can you provide some feedback on the status of those here in this thread?

👋 @Spaak and @bkrayfield - could you provide a short update to where you are in the review process?

Thanks so much!

[jeancmaia]

Hey @crvernon. I have addressed all the great feedback provided by @Spaak and refactored both the library and the paper.

Thanks!

[crvernon]

Thanks @jeancmaia!

[bkrayfield]

Hello @crvernon, end of semester work has slowed me down, but making progress. Should be rounding everything up this week.

[Spaak]

@crvernon The only remaining feedback I have is that the tutorial and paper could contain a little bit more motivating background on why an inference with an MCGLM model is more powerful (in some sense) than something univariate/classical. But I think that is also a matter of preference (related to the journal and its scope); the software itself is adequately documented. All other points have been taken care of!