Joss-reviews: [PRE REVIEW]: causal-curve: A Python Causal Inference Package to Estimate Causal Dose-Response Curves

[whedon]

Submitting author: @ronikobrosly (Roni Kobrosly)
Repository: https://github.com/ronikobrosly/causal-curve
Version: v0.3.2
Editor: @oliviaguest
Reviewers: @cmparlettpelleriti, @tomfaulkenberry, @alexjonesphd
Managing EiC: Kyle Niemeyer

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

@ronikobrosly 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).

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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:

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[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:

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

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[whedon]

Software report (experimental):

github.com/AlDanial/cloc v 1.84  T=0.09 s (389.8 files/s, 51520.2 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          17            512            609           1483
reStructuredText                11            292             80            561
Jupyter Notebook                 1              0            427            323
Markdown                         2             56              0            142
TeX                              1              8              0             53
DOS Batch                        1              8              1             26
YAML                             1              7              3             15
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            35            887           1127           2612
-------------------------------------------------------------------------------


Statistical information for the repository '2467' was gathered on 2020/07/10.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Roni Kobrosly                   44          4262           1658          100.00

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
Roni Kobrosly              2604           61.1          1.3               10.33

[whedon]

Reference check summary:

OK DOIs

- 10.1177/0962280209340213 is OK
- 10.2202/1557-4679.1181 is OK
- 10.1037/a0020761 is OK

MISSING DOIs

- https://doi.org/10.2202/1557-4679.1043 may be missing for title: Targeted maximum likelihood learning.

INVALID DOIs

- None

[whedon]

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

[ronikobrosly]

@whedon commands

On Fri, Jul 10, 2020 at 3:18 PM whedon [e-mail] wrote:

👉 Check article proof 📄 👈
https://github.com/openjournals/joss-papers/blob/joss.02467/joss.02467/10.21105.joss.02467.pdf

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You are receiving this because you were mentioned.
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[whedon]

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@whedon check references

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[kyleniemeyer]

Hi @cMadan, this is slightly outside your field, but could you edit this one?

[kyleniemeyer]

@whedon invite @cMadan as editor

[whedon]

@cMadan has been invited to edit this submission.

[ronikobrosly]

Hello, thanks so much for considering this work. I looked over the list of
possible reviewers and think the following people would be great, due to
their experience with causal inference, epidemiology, or psychology:

usernames:

seabbs
acolum
tomfaulkenberry

On Fri, Jul 10, 2020 at 3:17 PM whedon [e-mail] wrote:

Submitting author: @ronikobrosly https://github.com/ronikobrosly (Roni
Kobrosly http://orcid.org/0000-0003-0363-9662)
Repository: https://github.com/ronikobrosly/causal-curve
https://github.com/ronikobrosly/causal-curve
Version: v0.3.2
Editor: Pending
Reviewer: Pending
Managing EiC: Kyle Niemeyer

⚠️ JOSS reduced service mode ⚠️

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
https://blog.joss.theoj.org/2020/05/reopening-joss.

Author instructions

Thanks for submitting your paper to JOSS @ronikobrosly
https://github.com/ronikobrosly. Currently, there isn't an JOSS editor
assigned to your paper.

@ronikobrosly https://github.com/ronikobrosly 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
https://bit.ly/joss-reviewers 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 https://github.com/whedon is here to
help you find and assign reviewers and start the main review. To find out
what @whedon https://github.com/whedon can do for you type:

@whedon commands

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[cMadan]

@kyleniemeyer, sorry, I don't think I can take on another right now.

[ronikobrosly]

@kyleniemeyer , is it okay to, say, add a sentence or make a small edit at this step in the process? Or should I hold off until reviewers give feedback?

[kyleniemeyer]

@ronikobrosly yes, feel free to make edits right now, since we are still working to find an editor and reviewers.

[ronikobrosly]

@whedon generate pdf

[whedon]

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

[ronikobrosly]

@whedon commands

[whedon]

Here are some things you can ask me to do:

# List Whedon's capabilities
@whedon commands

# List of editor GitHub usernames
@whedon list editors

# List of reviewers together with programming language preferences and domain expertise
@whedon list reviewers

EDITORIAL TASKS

# Compile the paper
@whedon generate pdf

# Compile the paper from alternative branch
@whedon generate pdf from branch custom-branch-name

# Ask Whedon to check the references for missing DOIs
@whedon check references

# Ask Whedon to check repository statistics for the submitted software
@whedon check repository

[ronikobrosly]

@whedon check references

[whedon]

Reference check summary:

OK DOIs

- 10.1177/0962280209340213 is OK
- 10.2202/1557-4679.1181 is OK
- 10.1037/a0020761 is OK

MISSING DOIs

- https://doi.org/10.2202/1557-4679.1043 may be missing for title: Targeted maximum likelihood learning.

INVALID DOIs

- None

[oliviaguest]

@whedon assign @oliviaguest as editor

[whedon]

OK, the editor is @oliviaguest

[oliviaguest]

@whedon assign @tomfaulkenberry as reviewer

[whedon]

OK, @tomfaulkenberry is now a reviewer

[oliviaguest]

@ronikobrosly when you get a sec, please add the missing DOI and then recompile the PDF using the @whedon generate pdf command. ☺️

[ronikobrosly]

of course @oliviaguest !

[ronikobrosly]

@whedon generate pdf

[whedon]

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

[ronikobrosly]

@whedon check references

[whedon]

Reference check summary:

OK DOIs

- 10.1177/0962280209340213 is OK
- 10.2202/1557-4679.1181 is OK
- 10.1037/a0020761 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[ronikobrosly]

@oliviaguest , because it was a Berkeley internal dept paper and it seems like the other TMLE reference covers it I ended up removing that reference.

[oliviaguest]

@ronikobrosly awesome and thanks!

[oliviaguest]

@whedon assign @cmparlettpelleriti as reviewer

[whedon]

OK, @cmparlettpelleriti is now a reviewer

[oliviaguest]

@whedon add @tomfaulkenberry as reviewer

[whedon]

OK, @tomfaulkenberry is now a reviewer

[oliviaguest]

@whedon add @cmparlettpelleriti as reviewer

[whedon]

OK, @cmparlettpelleriti is now a reviewer

[oliviaguest]

@whedon add @alexjonesphd as reviewer

[whedon]

OK, @alexjonesphd is now a reviewer

[oliviaguest]

@whedon start review

[whedon]

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/2523.

[oliviaguest]

👋 @cmparlettpelleriti, @tomfaulkenberry, @alexjonesphd: please go to #2523 to get the review started! ✨