Improved regression in ratio type estimators based on robust M-estimation

Khalid Ul Islam Rather; Eda Gizem Koçyiğit; Ronald Onyango; Cem Kadilar

doi:10.1371/journal.pone.0278868

Peer Review History

Original SubmissionOctober 18, 2022
2 Nov 2022 Decision Letter - Nadia Hashim Al-Noor, Editor PONE-D-22-27634Improved Regression in Ratio Type Estimators Based on Robust M-EstimationPLOS ONE Dear Dr. RATHER, 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. ============================== ACADEMIC EDITOR: The manuscript needs major revision. ============================== Please submit your revised manuscript by Dec 17 2022 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. 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Please do not edit.] 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: Yes Reviewer #3: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ****** 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 Reviewer #3: Yes ****** 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 Reviewer #3: Yes ****** 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: To improve the novelty of the manuscript, some other objective functions should also be used. The real data application to demonstrate the application of the proposal should be the part of the paper. The overall language of the paper needs an improvement. Reviewer #2: Referee report: After reviewing the related literature in detail, authors develop a new family of the robust ratio estimators using the Uk’s redescending M-estimator successfully. In both application and simulation study, it is found that the proposed family is the most efficient estimator according to estimators in literature. As authors mention, these results support the theoretical efficiency condition obtained in (21). Authors derives two conditions from (21) but these conditions should be corrected as follows: From (21), B-B_UK+2R_j+B+B_UK-2b>0, 2B+2R_j-2b>0, R_j>b-B. Authors should evaluate the results of application and simulation based on the theoretical efficiency condition: R_j>b-B. After revising the manuscript according to the mentioned correction, the manuscript can be published in Plos One. Reviewer #3: The authors propose a new robust ratio type estimator using the Uk’s redescending M-estimator is proposed for the estimation of the finite population mean in the simple 24 random sampling (SRS) when there are outliers in the dataset. The properties of the proposed estimators are obtained and compared with the properties of the existing estimators. The theoretical results are enhanced empirically. Although, theoretical and computational results are found satisfactory but, the paper is not suitable for publication in its current form. It needs revision under the comments highlighted in the pdf file attached in the attachment section. ****** 6. 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 Reviewer #3: 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. Attachments Attachment Submitted filename: reportplosone.pdf Attachment Submitted filename: reportplosone.docx Attachment Submitted filename: PONE-D-22-27634_comments.pdf https://doi.org/10.1371/journal.pone.0278868.r001
Revision 1
7 Nov 2022 Author Response Reviewer #1: To improve the novelty of the manuscript, some other objective functions should also be used. The real data application to demonstrate the application of the proposal should be the part of the paper. The overall language of the paper needs an improvement. Dear Reviewer I , Thank you for your review and contributions. We started this work with the aim of developing the estimator proposed by Noor-ul Amin et al.(2020). The methods proposed before 2020 have already been compared in that article and it has been shown that the proposed ratio estimator is better than the estimators in the literature. We consider it sufficient to show that our proposed estimator is better than the proposed method in 2020. However, we expanded the Introduction section and gave the existing estimators. In our study, there are already real data studies in addition to the simulation study. If what you are talking about is solving numerical calculations step by step, this is quite difficult and complex due to objective functions. For this reason, we did all the operations on the R program and shared the codes with the journal. We have worked on the changes you mentioned. We hope that the revised version of the work will satisfy you. Regards. Reviewer #2: After reviewing the related literature in detail, authors develop a new family of the robust ratio estimators using the Uk’s redescending M-estimator successfully. In both application and simulation study, it is found that the proposed family is the most efficient estimator according to estimators in literature. As authors mention, these results support the theoretical efficiency condition obtained in (21). Authors derives two conditions from (21) but these conditions should be corrected as follows: From (21), B-B_UK+2R_j+B+B_UK-2b>0, 2B+2R_j-2b>0, R_j>b-B. Authors should evaluate the results of application and simulation based on the theoretical efficiency condition: R_j>b-B. After revising the manuscript according to the mentioned correction, the manuscript can be published in Plos One. Dear Reviewer II , Thank you for your review and contributions. The expression "+" is misspelled in the formula in the equation you specified. The same equation has been written more clearly and corrected. Regards. Reviewer #3: The authors propose a new robust ratio type estimator using the Uk’s redescending M-estimator is proposed for the estimation of the finite population mean in the simple 24 random sampling (SRS) when there are outliers in the dataset. The properties of the proposed estimators are obtained and compared with the properties of the existing estimators. The theoretical results are enhanced empirically. Although, theoretical and computational results are found satisfactory but, the paper is not suitable for publication in its current form. It needs revision under the comments highlighted in the pdf file attached in the attachment section. Dear Reviewer III , Thanks for your careful review and advice. The corrections you requested have been made. We have made corrections based on your comments. The revised version of the paper has been submitted as a "Manuscript" file, and you can see changes with the highlighted version on the "Revised Manuscript with Track Changes" file your notes have been answered on “PONE-D-22-27634 response to comments” pdf file. Regards. Attachments Attachment Submitted filename: Response to Reviewers.pdf https://doi.org/10.1371/journal.pone.0278868.r002
22 Nov 2022 Decision Letter - Nadia Hashim Al-Noor, Editor PONE-D-22-27634R1 Improved Regression in Ratio Type Estimators Based on Robust M-Estimation PLOS ONE Dear Dr. RATHER,, 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. ============================== ACADEMIC EDITOR: Revise your manuscript according to reviewers comments. Also, revise your introduction section by mentioning the latest related publish papers. The following papers can also be discussed.ShahzadU,AlnoorNH,HanifM,SajjadI,AnasMM.Imputationbasedmeanestimatorsincaseofmissing data utilizing robust regression and variance-covariance matrices. Communications in StatisticsSimulation and Computation. 2020a. 32. ShahzadU,AlnoorNH,HanifM,SajjadI,AnasMM.Quantileregression-ratio-typeestimators for mean estimation under complete and partial auxiliary information. Scientia Iranica. 2020b. https://doi.org/10.24200/sci.2020.54423.3744/ ============================== Please submit your revised manuscript by Jan 06 2023 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: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] <p 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 #2: All comments have been addressed Reviewer #3: (No Response) ******** 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 #2: Yes Reviewer #3: Partly ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes Reviewer #3: 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 #2: Yes Reviewer #3: Yes ****** 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 #2: Yes Reviewer #3: 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 #2: Manuscript is well now. All the changes are correct as per suggestion, can be published in your reputed journal PLOS. Reviewer #3: Review report Title: Improved regression in ratio type estimators based on robust M-estimation The authors have successfully incorporated the comments; however, the introduction section needs to be revised by incorporating the latest related references published till date. The following references can also be added to enhance the readability of the paper. Bhushan, S. and Kumar, A. (2022). Novel log type class of estimators under ranked set sampling. Sankhya B, 84, 421-447. https://doi.org/10.1007/s13571-021-00265-y Bhushan, S., Kumar, A., Shahab, S., Lone, S.A. and Almutlak, S.A. (2022). Modified class of estimators using ranked set sampling. Mathematics, 10, 3921, 1-13 Bhushan, S., Kumar, A. and Lone, S.A. (2022). On some novel classes of estimators under ranked set sampling. AEJ-Alexandria Engineering Journal, 61, 5465-5474. https://doi.org/10.1016/j.aej.2021.11.001. Bhushan, S., Kumar, A., Pandey, A.P. and Singh, S. (2022). Estimation of population mean in presence of missing data under simple random sampling. Communications in Statistics - Simulation and computation. https://doi.org/10.1080/03610918.2021.2006713 Bhushan, S., Kumar, A. and Singh, S. (2021). Some efficient classes of estimators under stratified sampling. Communications in Statistics - Theory and Methods, 1-30. DOI:10.1080/03610926.2021.1939052. Bhushan, S., Kumar, A., Akhtar, M.T. and Lone. S.A. (2022). Logarithmic type predictive estimators under simple random sampling. AIMS Mathematics, 7(7), 11992-12010. Bhushan, S., Kumar, A., Shahab, S., Lone. S.A. and Akhtar, M.T. (2022). On efficient estimation of population mean under stratified ranked set sampling. Journal of Mathematics, 2022(3), 1-20. Bhushan, S., Kumar, A., Onyango, R. and Singh, S. (2022). Some improved classes of estimators in stratified sampling using bivariate auxiliary information. Journal of Probability and Statistics, 2022(2), 1-23. Bhushan, S., Kumar, A., Singh, S. and Kumar, S. (2021). An improved class of estimators of population mean under simple random sampling. Philippine Statistician, 70(1), 33-47. ****** 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 #2: No Reviewer #3: 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.</p Attachments Attachment Submitted filename: Review report.docx https://doi.org/10.1371/journal.pone.0278868.r003
Revision 2
23 Nov 2022 Author Response RESPONSE TO REVIEWERS Reviewer #2: Manuscript is well now. All the changes are correct as per suggestion, can be published in your reputed journal PLOS. Dear Reviewer II, Thank you for your careful review and valuable contribution to our paper in this process. Regards. Reviewer #3: The authors have successfully incorporated the comments; however, the introduction section needs to be revised by incorporating the latest related references published till date. The following references can also be added to enhance the readability of the paper. Bhushan, S. and Kumar, A. (2022). Novel log type class of estimators under ranked set sampling. Sankhya B, 84, 421-447. https://doi.org/10.1007/s13571-021-00265-y Bhushan, S., Kumar, A., Shahab, S., Lone, S.A. and Almutlak, S.A. (2022). Modified class of estimators using ranked set sampling. Mathematics, 10, 3921, 1-13 Bhushan, S., Kumar, A. and Lone, S.A. (2022). On some novel classes of estimators under ranked set sampling. AEJ-Alexandria Engineering Journal, 61, 5465-5474. https://doi.org/10.1016/j.aej.2021.11.001. Bhushan, S., Kumar, A., Pandey, A.P. and Singh, S. (2022). Estimation of population mean in presence of missing data under simple random sampling. Communications in Statistics - Simulation and computation. https://doi.org/10.1080/03610918.2021.2006713 Bhushan, S., Kumar, A. and Singh, S. (2021). Some efficient classes of estimators under stratified sampling. Communications in Statistics - Theory and Methods, 1-30. DOI:10.1080/03610926.2021.1939052. Bhushan, S., Kumar, A., Akhtar, M.T. and Lone. S.A. (2022). Logarithmic type predictive estimators under simple random sampling. AIMS Mathematics, 7(7), 11992-12010. Bhushan, S., Kumar, A., Shahab, S., Lone. S.A. and Akhtar, M.T. (2022). On efficient estimation of population mean under stratified ranked set sampling. Journal of Mathematics, 2022(3), 1-20. Bhushan, S., Kumar, A., Onyango, R. and Singh, S. (2022). Some improved classes of estimators in stratified sampling using bivariate auxiliary information. Journal of Probability and Statistics, 2022(2), 1-23. Bhushan, S., Kumar, A., Singh, S. and Kumar, S. (2021). An improved class of estimators of population mean under simple random sampling. Philippine Statistician, 70(1), 33-47. Dear Reviewer III, Thank you for your careful review and valuable contribution to our paper in this process. The latest related references you mentioned in your comments have been added to the "Introduction" section of the manuscript. Regards. RESPONSE TO ACADEMIC EDITOR ACADEMIC EDITOR: Revise your manuscript according to reviewers comments. Also, revise your introduction section by mentioning the latest related publish papers. The following papers can also be discussed. Shahzad U, Alnoor NH, Hanif M, Sajjad I, Anas MM. Imputation based mean estimators in case of missing data utilizing robust regression and variance-covariance matrices. Communications in Statistics Simulation and Computation. 2020a. 32. Shahzad U, Alnoor NH, Hanif M,Sajjad I,Anas MM. Quantileregression-ratio-type estimators for mean estimation under complete and partial auxiliary information. Scientia Iranica. 2020b. https://doi.org/10.24200/sci.2020.54423.3744/ Dear Academic Editor, Thank you for your contribution to our paper. We revised the manuscript according to the reviewers' comments. Also, the cited references you pointed out have been added to the "Introduction" section. Regards. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0278868.r004
28 Nov 2022 Decision Letter - Nadia Hashim Al-Noor, Editor Improved Regression in Ratio Type Estimators Based on Robust M-Estimation PONE-D-22-27634R2 Dear Mr. Rather, 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, Nadia Hashim Al-Noor, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0278868.r005
Formally Accepted
1 Dec 2022 Acceptance Letter - Nadia Hashim Al-Noor, Editor PONE-D-22-27634R2 Improved regression in ratio type estimators based on robust M-estimation Dear Dr. Rather: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Nadia Hashim Al-Noor Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0278868.r006

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