PONE-D-20-14520

Time effects of bacterial vaginosis on infant morbidities in Kenya assessed using modified skewed generalized estimating equations

PLOS ONE

Dear Dr. Mwenda,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Kind regards,

Musie Ghebremichael

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: No

Reviewer #2: Partly

Reviewer #3: Partly

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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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: No

Reviewer #2: No

Reviewer #3: No

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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: No

Reviewer #2: Yes

Reviewer #3: 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 main focus of this article is to implement a non-standard GLM/GEE method to analyze the infant morbidity and mortality, due to skewness of data. The authors incorporate Burr Type X (generalized Rayleigh) distribution and geeM package in R to achieve this goal.

My main concern is with the Methodology. I recommend that the authors focus on how the statistical analysis was implemented in geeM package of R, rather than going over the general technical details (see below). For this, the authors should understand the geeM package better, in order to make clearer and better technical arguments. In particular, the article will be more attractive if the authors include the R codes, either in the text or in the appendix/supplemental material.

For specific comments, there are instances where things could be eliminated or moved to the appendix. For example, the explanations from line 244 to 280 are standard in GLM and can be found in many books and articles, so the authors can just give a reference without having to explain in 3 pages.

Also, the notations are very inconsistent throughout. The both the X's and Y's are sometimes capital letters and sometimes lower case letters and sometimes bold letters; in both cases the subscripts are either inconsistent or non-existent. In addition, authors sometimes use X^T and other times X' to denote the X transpose. More seriously, the formulas (3) and (4), as well as the formula on line 309, are incorrect. These inconsistencies make the paper very difficult to read and make sense.

Again, the authors must take care to make the technical arguments coherent and sound. By focusing more on understanding and implementing the R package that actually perform the analysis, the hope is that the paper will become more consistent and practical.

Reviewer #2: See attached

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) (Limit 200 to 20000 Characters)

Reviewer #3: This study uses data from the Nairobi infant morbidity study to evaluate the effects of time and bacterial vaginosis (BV) on morbidity among infants born to women infected with HIV-1. The authors compared the results of their data analysis using a traditional generalized estimating equations (GEE) model versus their newly-developed skewed generalized estimating equations (SGEE) model, which extends the GEE framework to accommodate possible asymmetry.

General comments

It is unclear if the authors are presenting a novel statistical method versus a novel application of an existing method to shed light on the effects of time and VB on infant mortality. Note that lines 182-184 suggest the former while lines 137-139 and 455-456 suggest the latter.

If the formulation of their SGEE model is novel, it would be helpful to formally validate the utility of this method (versus GEE) is the presence of asymmetry using simulation studies. If this work has already been done and published elsewhere, and the authors are presenting a novel application of this method, I’m wondering if it would be possible to exclude the majority of the technical information contained in the methods section (or at least move it to an appendix), and report a validated goodness of fit/model comparison measure for the GEE versus SGEE models applied to their data.

Specific comments

Introduction:

-Line 40: I’m not sure what is meant by “distorted” in this sentence. Do the authors mean “transformed”?

-Lines 42-44: “A typical assumption for the distribution of the error term in logistic analysis is the logistic function that is commonly applied to data with standard binomial distributions.” I believe the phrasing that suggests logistic regression models have error variables that follow a logistic distribution is characteristic of discrete choice models, primarily used by economists. Given that this paper involves a biomedical application (and will likely appeal to a clinical audience) it would be helpful to rephrase.

-Line 58: “The supporting literature has shown that this could be inefficient for parameter estimation in some settings” could use a supporting reference.

Methods:

-The notation introduced at the beginning of the methods section is ambiguous. For example, line 146 introduces “nj” as the number of observations observed for subject “i”. Later, the notation “ni” is used to denote the dimension of the covariate matrix and response vector. Repeated use of the same letter with varying subscripts is confusing. Elsewhere (line 150) the authors use Yij to (presumably) denote the jth observation for subject i, but then two lines later (line 152) define “Yi” as an indicator for subject i’s morbidity without reference to a particular time. This suggests that the authors are modeling a univariate response. Was the second subscript j left off in line 152?

-Line 149: I’m not sure what a matrix-vector is? Do they mean covariate matrix?

-Line 188: Y0 is not defined.

Results

-Line 342: It would be good to explicitly state how the response variable was categorized (e.g. 0 vs at least 1 morbidity at a given monthly visit)

-Line 352: Since the authors are interested in comparing morbidity by month among infants born to mothers with vs without BV, it would be easier to digest Table 1 if it presented the percentage of infants with at least one morbidity conditional on BV status during each month. For example, during month 1 a direct calculation of the 115/(115+33)=78% of infants experiencing a morbidity within the BV-present group vs the 85/(85+94)=47% of infants experiencing a morbidity within the BV-absent group highlights the relevant comparison more clearly.

-Line 357: “important to examine the effect of BV on child morbidity” should add “over time”

-Line 358: Was data from birth through 6 months used in this analysis (as stated in line 325)? Here t=1,2,…,6 suggests data from birth was not used.

-Line 364: “We wanted to show that our model fits better for binary data that violate symmetry”. As noted above, this general goal is better achieved using simulations.

-Line 365: “We tested different correlation structures for comparison purposes; however, because our model was concerned with the time effect, we used the AR(1) output for interpretation” This point could be clarified and could use some elaboration. How did the correlation structures compare overall? How is the use of AR(1) beneficial regarding modeling the effect of time in this application? Is it because measurements taken further apart have lower correlation according to the pattern imposed by AR(1)?

-Line 381: Where is -0.372 coming from? The coefficient for sex using the SGEE model with AR(1) is -0.369. Also, it would be helpful to explicitly note that this is an odds ratio (line 380).

-Line 381: “Those with BV had a 4.48 odds of morbidity compared with their counterparts” is this the OR at birth? I am not sure how this OR is interpreted because time is coded as t = 1, 2, ..,6 (358) and there is an interaction term. Did the authors use data at birth (time =0)?

-Line 386: The authors should explicitly state that the quantity they are using in an OR.

-Line 392 (and Table 3): Again, was data from birth used in this application or is the effect being extrapolated? (again, line 358 suggests outcome measurements were at months 1-6)

-Line 395: Where is the quantity 2.72 coming from? Isn’t the OR 3.37? And should 1.04 be 1.11?

Discussion

-Line 410: Best to avoid causal language such as “proved”.

-Line 419: Again, avoid using the word “proven”.

-Line 451: “In addition, our study found a decline in the number of morbidities from birth” Table 1 suggests that there was a decline in morbidity (defined as no morbidity vs at least 1 morbidity) over time among infants in the BV-positive group but an increase in morbidity over time among infants in the BV-negative group.

-Lines 461-463: “Asymmetry in the binary outcome is a phenomenon that should be appropriately accounted for in analytical models to avoid biases in final parameter estimates, as has been established in Table 2” It’s a stretch to draw this conclusion based on an inspection of p-values from just one application. The authors should cite simulation studies using their exact formulation of the SGEE model or validated measures of fit applied to this data.

-Line 464: I believe the term “converges” should be replaced with “is equivalent”

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Attachments

Attachment

Submitted filename: plos_one_jul_20.pdf

PONE-D-20-14520R1

Skewed-Logit model for Analyzing Correlated Infants morbidity data

PLOS ONE

Dear Dr. Mwenda,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 30 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Musie Ghebremichael

Academic Editor

PLOS ONE

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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: (No Response)

Reviewer #2: (No Response)

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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: Partly

**********

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: No

Reviewer #2: No

**********

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: For the GEE model, it would be helpful to show additional details of model selection. Authors may consider using QIC or QICu functions in R package MuMIn.

On page 18, equation (9), there should only be 6 main effects. I think beta_4 is redundant. Also, for the interaction term, it is more customary to write beta_{15} with (BV X time).

Again, providing the computer code will be very much appreciated.

Reviewer #2: My comments have been addressed except my second comment, beginning "The application of the scobit method to the data should include some justification based on the data, before seeing results ..." The authors reply in their letter with a justification for using scobit that is independent of the results of the data analysis. This argument, based on earlier medical analyses, satisfied me. However, I don't know whether they included this key justification in the revision of the paper; perhaps I missed it.

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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: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Skewed-Logit model for Analyzing Correlated Infants morbidity data

PONE-D-20-14520R2

Dear Dr. Mwenda,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Musie Ghebremichael

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

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Reviewers' comments: