PONE-D-22-03933Bayesian model averaging for nonparametric discontinuity designPLOS ONE

Dear Dr. Hinne,

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Academic Editor

PLOS ONE

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Additional Editor Comments:

The authors must address all the issues raised by the reviewer. The paper is recommended for major revision.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper presents a framework for discontinuity-based designs using Bayesian model averaging and Gaussian process regression. It is a topic of interest to the researchers in the related areas. For the reader, however, a number of points need clarifying and certain statements require further justification. My detailed comments are as follows:

(1)In the abstract section, the quantification proposed by the authors supporting the innovation point of either model is crucial to solve the main problem of the average of Bayesian models, because the prior probabilities of different models greatly affect the results of the Bayesian model averaging method, and the authors please describe them in detail in this section.

(2)Is this article more applicable to the discontinuity model?The study of continuous models is not comprehensive and detailed, does this paper focus on the description of discontinuous models?

(3)It is noteworthy that your paper requires careful editing of the format.There are many problems in the paper format, such as the first line of the paragraph, multiple syntax errors, etc.

Reviewer #2: This paper is quite interesting paper working on nonparametric discontinuity design with Bayesian model averaging. Previous approaches have overconfidence from the implicit consumptions and model misspecification from the overly simplified regression models. To overcome these shortcomings, this paper proposes a framework of discontinuity-based designs using Bayesian model averaging and Gaussian process regression, namely, Bayesian nonparametric discontinuity design' (BNDD).

This paper demonstrated the usage of BNDD in multiple promising simulations, such as the effects of winning an election and longevity, phantom border effect on Dutch government elections, and Kundalini meditation effect on heart rate.

The paper is also well written and structured, and it is easy to follow.

One minor doubt for me is the paper assume the distribution is Gaussian distribution, and thus Gaussian process is used in the paper. Is possible real world simulation is not under Gaussian distribution, and thus can not be used in Gaussian process?

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Reviewer #1: No

Reviewer #2: No

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Bayesian model averaging for nonparametric discontinuity design

PONE-D-22-03933R1

Dear Dr. Hinne,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Lalit Chandra Saikia, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This paper can be accepted, the research in this paper is interesting, and the authors have done enough work.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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