PONE-D-20-14450

Multiple imputation of maritime search and rescue data at multiple missing patterns

PLOS ONE

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Academic Editor

PLOS ONE

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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: Partly

Reviewer #2: Partly

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

Reviewer #1: No

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: No

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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: This paper uses multiple imputation methods to deal with the missing data of marine search and rescue, and verifies the effect of multiple imputation in different missing patterns, but the article lacks novelty and general significance.

1.The authors do not reference original sources, such as seminal work by Rubin done in 1970's on multiple imputation.

2.This article compares the effect of DA algorithm and EMB algorithm on the processing of missing data, but it does not highlight the particularity of maritime search and rescue data.

3.Please clarify your significant contributions besides utilizing existing algorithms for handling missing data.

4.It has to be described if the algorithm used in this article is better than data imputation based on professional experience in the field of maritime search and rescue.

5.The article only imputation the missing data within five years. Will it affect the results in the case of a long time series?

Here are some clerical mistakes:

1.Delete “based on” on line 45.

2.Irregular chart format in table 5.

3.The figures are not clear.

Reviewer #2: Well known multiple imputation method and algorithms are properly applied. Data and results clearly presented in figures.

1.In case of some variables the general sense of applying this method for SAR purposes rises questions and reservations:

1) “Death” (“Death is the number of missing or dead persons”).

What is a purpose of assessing (or receiving) number of “death” (in previous years) by statistical methods?

Who (or what kind of institution) is interested in receiving such data?

2) “Weather” (“Weather is the number of bad weather”)

To be defined what is “bad weather” – e.g. wind force higher than 8° B, 10°B, sea state, tropical storms, poor visibility?

Why do the Authors try to input missing data by statistical methods instead of checking real meteorological surface analysis existing in the shipping world and other meteorological data bases?

3) “Volume” (“Volume is the volume of waterborne transport”)

Figure 6 . Observed versus imputed Value of Volume -

What are the units? ( e.g. 75000 - individual ships observed/ analyzed?)

4) “TR” (“TR is the times of distress”)

Units again.

E.g. What is TR 200? (Figure 6)

2.Other remarks:

1) Table 1. “Safety status” to be used rather than “Security status”, as the word “Security” is used in shipping for piracy and maritime terrorism issues.

2) Figure 4 - axes x - missing labels at 30% missing rate.

3) Generally clear and understandable language, but some sentences require language corrections (including professional maritime vocabulary) as they are difficult to understand (e.g. In 2018, China had a total of 176 water traffic accidents with general and higher levels associated with transportation ships, causing 237 people missing, 83 shipwrecks, and a direct economic loss of 290 million yuan [4-5].)

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Reviewer #1: No

Reviewer #2: No

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Attachments

Attachment

Submitted filename: Comments.docx

Multiple imputation of maritime search and rescue data at multiple missing patterns

PONE-D-20-14450R1

Dear Dr. JIANG

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,

Lubos Buzna, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Both reviewers recognized that the paper has been significantly improved and do not have any additional significant comments. I suggest authors to check remaining minor comments of Reviewer 1, in particular those suggesting some additional explanations.

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

Reviewer #2: 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

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: 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

Reviewer #2: 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

Reviewer #2: Yes

**********

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: 1. The label of the article formula should be aligned as much as possible

2. The calculation process of the EMB algorithm in Figure 1 needs to be explained in more detail, including the meaning of different colors and different graphic annotations in the figure, etc.

3. The units of the parameter variables in Table 2 to Table 5 need to be explained

4. In the article, “Weather” represents the number of bad weather, and the meaning or indicators of bad weather need to be explained

Reviewer #2: The article presents very valuable research results. All reservations were clearly explained. All questions were answered to my satisfaction. Small were corrections done as indicated.

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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

Reviewer #2: Yes: Miroslaw Wielgosz