[REVIEW]: **geostan**: An R package for Bayesian spatial analysis

editorialbot commented 2 years ago

Submitting author: !--author-handle-->@ConnorDonegan@jbytecode<!--end-editor-- Reviewers: @wcjochem, @becarioprecario Archive: 10.5281/zenodo.7311716

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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 @becarioprecario

📝 Checklist for @wcjochem

editorialbot commented 2 years ago

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editorialbot commented 2 years ago

Software report:

github.com/AlDanial/cloc v 1.88  T=0.11 s (828.9 files/s, 146986.2 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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R                               29            213           2464           3141
TeX                              3             63              0            493
CSS                              3             98             52            442
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Markdown                         3             93              0            240
Rmd                              3            191            295            125
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SVG                              1              0              1             11
Bourne Shell                     2              4              2              4
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SUM:                            93           2029           2984          11479
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gitinspector failed to run statistical information for the repository

editorialbot commented 2 years ago

Wordcount for paper.md is 1047

editorialbot commented 2 years ago

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

OK DOIs

- 10.31219/osf.io/3ey65 is OK
- 10.1016/j.spasta.2020.100450 is OK
- 10.3390/ijerph18136856 is OK
- 10.2307/2532039 is OK
- 10.1111/j.1467-8306.2005.00484.x is OK
- 10.1016/C2017-0-01015-7 is OK
- 10.1111/j.1538-4632.2007.00708.x is OK
- 10.1016/j.apgeog.2013.08.013 is OK
- 10.1007/s13524-016-0499-1 is OK
- 10.1016/j.csda.2008.07.033 is OK
- 10.1002/(sici)1097-0258(19970415)16:7<741::aid-sim501>3.0.co;2-1 is OK
- 10.1002/(sici)1097-0258(19980930)17:18<2025::aid-sim865>3.0.co;2-m is OK
- 10.1111/j.2517-6161.1974.tb00999.x is OK
- 10.1007/BF00116466 is OK
- 10.1177/0962280216660421 is OK
- 10.1016/j.sste.2019.100301 is OK
- 10.18637/jss.v063.i18 is OK
- 10.1080/10618600.2016.1172487 is OK
- 10.5281/zenodo.1308151 is OK
- 10.18637/jss.v092.i10 is OK
- 10.1214/17-BA1091 is OK
- 10.1111/j.1538-4632.1995.tb00338.x is OK

MISSING DOIs

- None

INVALID DOIs

- None

editorialbot commented 2 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

jbytecode commented 2 years ago

Dear @wcjochem and @becarioprecario

This is the review thread. Firstly, type

@editorialbot generate my checklist

to generate your own checklist. In that checklist, there are 20 check items. Whenever you complete the corresponding task, you can check off them. The review process is interactive so you can always interact with the authors, reviewers, and the editor. You can also create issues and pull requests in the target repo. Please do mention this thread's URL in the issues so we can keep tracking what is going on out of our world.

Please do not hesitate to ask me anything, anytime.

Thank you in advance!

jbytecode commented 2 years ago

Dear @wcjochem and @becarioprecario

Could you please update your status on how is going your review and generate your task lists?

Thank you in advance.

jbytecode commented 2 years ago

@editorialbot remind @wcjochem in two days

editorialbot commented 2 years ago

Reminder set for @wcjochem in two days

jbytecode commented 2 years ago

@editorialbot remind @becarioprecario in two days

editorialbot commented 2 years ago

Reminder set for @becarioprecario in two days

jbytecode commented 2 years ago

Thanks @editorialbot !

editorialbot commented 2 years ago

You are welcome

editorialbot commented 2 years ago

:wave: @wcjochem, please update us on how your review is going (this is an automated reminder).

editorialbot commented 2 years ago

:wave: @becarioprecario, please update us on how your review is going (this is an automated reminder).

ConnorDonegan commented 2 years ago

@editorialbot generate pdf

editorialbot commented 2 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

jbytecode commented 2 years ago

@wcjochem, @becarioprecario - could you please update your status?

Can I kindly ask you to create your check list first?

Thank you in advance.

wcjochem commented 2 years ago

Hi @jbytecode when I agreed to review this submission I said I couldn't start until after 15 September. So I have only started my review and it is ongoing. Thanks.

jbytecode commented 2 years ago

@wcjochem - I am so sorry for bothering and pinging you too much, my bad! I totally forgot your deadline. Thank you for reminding that.

jbytecode commented 1 year ago

@becarioprecario - could you please update your status? We have failed to get a life signal from you. Setting a deadline for us would be great, if possible. Thank you in advance.

jbytecode commented 1 year ago

Dear @becarioprecario,

This is the last reminder. Since you never sent a response, I assume that you are so much busy to reply messages, and/or you are not able to receive notifications. If you don't set a deadline for us until 15th October, I will try to find another reviewer for this issue.

Thank you in advance.

becarioprecario commented 1 year ago

Hi,

Sorry for the delay. I will try to send the review by the end of the week.

Best,

Virgilio

El 13 oct 2022, a las 11:20, Mehmet Hakan Satman @.**@.>> escribió:

Dear @becarioprecariohttps://github.com/becarioprecario,

This is the last reminder. Since you never sent a response, I assume that you are so much busy to reply messages, and/or you are not able to receive notifications. If you don't set a deadline for us until 15th October, I will try to find another reviewer for this issue.

Thank you in advance.

— Reply to this email directly, view it on GitHubhttps://github.com/openjournals/joss-reviews/issues/4716#issuecomment-1277299612, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ABYD6WSVIO4RWQRSZ6H5V7LWC7H6DANCNFSM573GXAFQ. You are receiving this because you were mentioned.Message ID: @.***>

jbytecode commented 1 year ago

@becarioprecario - I am happy to hear from you. I will be waiting for your review. Thank you for the response.

becarioprecario commented 1 year ago

Review checklist for @becarioprecario

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/ConnorDonegan/geostan?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@ConnorDonegan) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] 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.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] 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

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] 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

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

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] 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?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] 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?

becarioprecario commented 1 year ago

I have read the paper now. These are some comments that perhaps require changes in the main paper:

Authorship. The geostan package has been vdeveloped by two authors but only one appears listed in the paper. Is there any particular reason for this?
BayesX is also an R package to fit Bayesian spatial models that should be mentioned.
Lines 55-59. Does the package relies on other R packages to compute these statistics and plots?
Line 74. If there is a model that will be included in a forthcoming version I would wait to have these models implemented to actually publish the paper. It seems that the SAR model is already there, so the paper can be updated and this sentence rephrased.
Line 81. INLA can also include user-defined models
Citation format. When the references are included in a sentence which is between parentheses I believe that they are written using the wrong formant, e.g., "(... Author1 et al. (2022) ...)" instead of "(... Autho1 et al., 2022, ...)"

jbytecode commented 1 year ago

@ConnorDonegan - could you please apply the corrections as suggested by our reviewer? Thank you in advance.

ConnorDonegan commented 1 year ago

Thank you @becarioprecario and @jbytecode, I will respond and submit revisions by this Thursday (Oct. 20).

wcjochem commented 1 year ago

Review checklist for @wcjochem

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/ConnorDonegan/geostan?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@ConnorDonegan) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] 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.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] 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

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] 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

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

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] 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?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] 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?

ConnorDonegan commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

ConnorDonegan commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

ConnorDonegan commented 1 year ago

Thank you again @becarioprecario for your review.

authorship: I'm the only package author, although there are two contributors to the code base. Some of the Stan code that I use is from the published work of others, including contributor Mitzi Morris (ICAR models) and the regularized horseshoe prior used in the stan_esf model (from a paper by Pirronen and Vehtari). I do cite their work in the documentation. (I think that answers the question, but I'm eager to give credit in all appropriate ways.)
I now cite the R2BayesX Rackage
The spatial auto-correlation statistics do not rely on any outside packages. However, the package uses spdep and the Matrix package to create the connectivity matrices. I have revised the Functionality section to clarify how spdep is used and add reference to Matrix. Graphics are created using ggplot2, now cited.
The text now reflects that the SAR models are currently available.
I now cite INLA as among the packages that provide extensive customization. I believe this includes the ability to specify spatial ME models very similar to those in geostan (a spatial model as the prior distribution on the latent covariate, with user-provided measurement error variances.) @becarioprecario you may be able to correct me if I'm wrong about that.
After revisions, there is one citation that sits within parentheses (line 80). I believe it is done correctly, but will defer to @jbytecode

jbytecode commented 1 year ago

@becarioprecario - Do we have any issues about the corrections?

@wcjochem - could you please update your status? Do we have any progress?

Thank you in advance.

becarioprecario commented 1 year ago

Hi,

Thanks for your review.

I now cite INLA as among the packages that provide extensive customization. I believe this includes the ability to specify spatial ME models very similar to those in geostan (a spatial model as the prior distribution on the latent covariate, with user-provided measurement error variances.) @becarioprecariohttps://github.com/becarioprecario you may be able to correct me if I'm wrong about that.

Yes. INLA allows the user to define latent effects by specifying the distribution of these effects,

After revisions, there is one citation that sits within parentheses (line 80). I believe it is done correctly, and will defer to @jbytecodehttps://github.com/jbytecode

There is an extra bracket at the end that must be removed.

Best,

Virgilio

jbytecode commented 1 year ago

Dear all (@becarioprecario, @wcjochem, and @ConnorDonegan)

The review times of this submission is getting a little bit out of normal intervals.

I know we have tons of workload in our everyday life, but may I kindly request you to speed things up a bit?

Thank you in advance.

becarioprecario commented 1 year ago

Hi,

I just pointed out a typo in my last e-mail. Other than that, I think that the paper is fine.

Best,

Virgilio

jbytecode commented 1 year ago

@becarioprecario - you have still unchecked items in your task list. would you like me to check them on for you?

becarioprecario commented 1 year ago

@becarioprecariohttps://github.com/becarioprecario - you have still unchecked items in your task list. would you like me to check them on for you?

Thanks! I left them uncooked until the paper was revised. I have checked them now.

Best,

Virgilio

jbytecode commented 1 year ago

@becarioprecario - thank you so much for finalizing your review and consuming your time for JOSS.

wcjochem commented 1 year ago

@jbytecode I will finish my review this week. Thanks for your patience.

wcjochem commented 1 year ago

@ConnorDonegan and @jbytecode, thanks for the opportunity to review this work. This package is an impressive accomplishment and clearly you've put a lot of thought and work into it. I have been able to build (and test) and run through the code and models and review the manuscript. Overall it seems well done. I have a raised a few questions in https://github.com/ConnorDonegan/geostan/issues (and linked above) for your consideration. When those are addressed, I can complete my checklist.

jbytecode commented 1 year ago

@wcjochem - thank you for your comments

@ConnorDonegan - could you please apply the suggested changes

thank you in advance

ConnorDonegan commented 1 year ago

Many thanks for your review @wcjochem. I think the suggestion to break the geostan_fit methods documentation into a number of pages is a good idea. I'll do that and respond to your other comments, I think I can have that done by the middle of next week.

On the missing citation to support the performance claim (that the CAR models can work with all US county data interactively), I'll add a direct reference to my OSF preprint on `Building spatial CAR models'. The claim is a reference to the demonstration analysis in that paper, as well as the analysis of sampling efficiency in it. Thanks for catching that.

ConnorDonegan commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

ConnorDonegan commented 1 year ago

Thanks again @wcjochem for your review. I think you've already seen a notification for my responses to your comments over on the issues tab for the project github page.

I'll also leave a note of the changes here for everyone.

Performance claims

The manuscript states that the CAR model is efficient for fitting models to county-level data for the entire U.S. on a laptop (lines 83-86). Do you have a worked example for users that demonstrates that claim? Alternatively, please provide a reference in the manuscript to a paper where the model is used at that scale to provide evidence.

I've added a reference to the OSF pre-print "Building spatial conditional auto-regressive models in the Stan programming language" (https://osf.io/3ey65/) which has a demonstration analysis with US county data and also a study of sampling efficiency with head-to-head comparison between my Stan functions and NIMBLE's dcar proper.

Contributor guidelines

Please add clear guidance for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support.

I'm glad to be adding the following section to the paper:

User support and discussion

In addition to consulting the package website and vignettes (https://connordonegan.github.io/geostan), users are encouraged to engage with geostan through the package github page (https://github.com/connordonegan/geostan). The github "Issues" and "Discussions" tabs are the best place for users to seek support, ask questions, report bugs, or suggest new features. Contributions to the software can also be proposed by making a pull request to the github page.

`geostan_fit` methods documentation

Overall I found the functions to be adequately documented throughout; however, I think it could be improved if you could split the documentation for "geostan_fit methods" into separate pages for plotting/printing, extracting, predicting. Currently these are contained in a single documentation page and are indexed under one topic. These functions cover a wide range steps and it would be easier to find that documentation and I think it would make it more readable for users to have separate pages.

This is a really helpful suggestion. I see it was looking cluttered.

I've broken the geostan_fit methods documentation into the following pages:

This change to the documentation is now reflected on the website.

ConnorDonegan commented 1 year ago

@editorialbot generate pdf

editorialbot commented 1 year ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

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