[PRE REVIEW]: Hypothesize: Robust Statistics for Python

[whedon]

Submitting author: @Alcampopiano (Allan Campopiano) Repository: https://github.com/Alcampopiano/hypothesize Version: v1.0.0 Editor: @csoneson Reviewers: @martinagvilas, @arbennett Managing EiC: Arfon Smith

:warning: JOSS reduced service mode :warning:

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Author instructions

Thanks for submitting your paper to JOSS @Alcampopiano. Currently, there isn't an JOSS editor assigned to your paper.

@Alcampopiano if you have any suggestions for potential reviewers then please mention them here in this thread (without tagging them with an @). In addition, this list of people have already agreed to review for JOSS and may be suitable for this submission (please start at the bottom of the list).

Editor instructions

The JOSS submission bot @whedon is here to help you find and assign reviewers and start the main review. To find out what @whedon can do for you type:

@whedon commands

[whedon]

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

:warning: JOSS reduced service mode :warning:

Due to the challenges of the COVID-19 pandemic, JOSS is currently operating in a "reduced service mode". You can read more about what that means in our blog post.

For a list of things I can do to help you, just type:

@whedon commands

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

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[whedon]

Reference check summary:

OK DOIs

-  10.25080/Majora-92bf1922-00a  is OK

MISSING DOIs

- https://doi.org/10.1037/0003-066x.53.3.300 may be missing for title: How many discoveries have been lost by ignoring modern statistical methods?
- https://doi.org/10.1016/c2010-0-67044-1 may be missing for title: Introduction to robust estimation and hypothesis testing

INVALID DOIs

- None

[whedon]

:point_right: Check article proof :page_facing_up: :point_left:

[arfon]

@whedon commands

[whedon]

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# List all of Whedon's capabilities
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@whedon assign @username as reviewer

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@whedon add @username as reviewer

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@whedon re-invite @username as reviewer

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[arfon]

@whedon check repository

[whedon]

Software report (experimental):

github.com/AlDanial/cloc v 1.84  T=0.28 s (172.3 files/s, 30676.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          11           1362           1293           3446
Markdown                         9            933              0           1509
YAML                             2              9              4             69
TeX                              1              5              0             46
CSS                              1              3              0             19
Jupyter Notebook                25              0             25              0
-------------------------------------------------------------------------------
SUM:                            49           2312           1322           5089
-------------------------------------------------------------------------------

Statistical information for the repository '2193' was gathered on 2020/05/21.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Allan Campopiano                11          2024            153           23.55
alcampopiano                    57          5649           1419           76.45

Below are the number of rows from each author that have survived and are still
intact in the current revision:

Author                     Rows      Stability          Age       % in comments
Allan Campopiano           1749           86.4          2.0                2.69
alcampopiano               4352           77.0          0.8                3.81

[Alcampopiano]

Thank you very much for providing a list of potential reviewers. Starting from the bottom of that list, I have chosen the following reviewers based on their fields and programming language(s):

kirstensgithub martinagvilas alanfairless

I can continue to suggest more if needed.

[Alcampopiano]

@whedon check references

[arfon]

@whedon check references

[whedon]

Reference check summary:

OK DOIs

-  10.1037/0003-066X.53.3.300  is OK
-  10.1016/c2010-0-67044-1  is OK
-  10.25080/Majora-92bf1922-00a  is OK

MISSING DOIs

- None

INVALID DOIs

- None

[arfon]

:wave: @csoneson - could you edit this one for us? I'll go ahead and assign this to you now - please let me know if this is a problem.

[arfon]

@whedon assign @csoneson as editor

[whedon]

OK, the editor is @csoneson

[csoneson]

@whedon generate pdf

[whedon]

:point_right: Check article proof :page_facing_up: :point_left:

[csoneson]

👋@Alcampopiano - I will handle your submission and start by inviting reviewers. Going through your paper, I think it would be useful to include a brief comparison of Hypothesize to other (potential) Python packages implementing similar functionality. Could you add a statement about that?

[csoneson]

👋 @arbennett, @kirstensgithub, @martinagvilas - would you be interested in reviewing this submission for JOSS?

Hypothesize: Robust Statistics for Python

software: https://github.com/Alcampopiano/hypothesize accompanying paper: https://github.com/openjournals/joss-papers/blob/joss.02193/joss.02193/10.21105.joss.02193.pdf

[Alcampopiano]

I think it would be useful to include a brief comparison of Hypothesize to other (potential) Python packages implementing similar functionality. Could you add a statement about that?

@csoneson Absolutely. I will add a statement to that effect.

[martinagvilas]

@csoneson @Alcampopiano I would be glad to review this submission

[arbennett]

@csoneson @Alcampopiano - Sure, I'd be happy to review this!

[Alcampopiano]

Hello @csoneson,

As you have requested, I have added the following statements (and related references) regarding other useful Python libraries that offer methods for robust statistics:

While other statistical libraries in Python provide useful options for robust model fitting [@seabold2010statsmodels] and visualizations [@ho2019moving], Hypothesize focuses on providing a larger selection of robust methods for comparing groups and measuring associations, especially those that are analogous to traditional NHST approaches.

@whedon generate pdf

[arfon]

@whedon generate pdf

[arfon]

@Alcampopiano - commands to Whedon need to be in standalone comments ☝️

[whedon]

:point_right: Check article proof :page_facing_up: :point_left:

[csoneson]

@martinagvilas, @arbennett - brilliant, thank you for your quick replies. Since we now have two reviewers I'm going to start the actual review issue, where you will find your checklists and more details on the process.

[csoneson]

@whedon assign @martinagvilas as reviewer

[whedon]

OK, @martinagvilas is now a reviewer

[csoneson]

@whedon add @arbennett as reviewer

[whedon]

OK, @arbennett is now a reviewer

[csoneson]

@whedon start review

[whedon]

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/2241.