Responses

Download PDFPDF
Statistical approaches in published ophthalmic clinical science papers: a comparison to statistical practice two decades ago
Compose Response

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Statement of Competing Interests

PLEASE NOTE:

  • A rapid response is a moderated but not peer reviewed online response to a published article in a BMJ journal; it will not receive a DOI and will not be indexed unless it is also republished as a Letter, Correspondence or as other content. Find out more about rapid responses.
  • We intend to post all responses which are approved by the Editor, within 14 days (BMJ Journals) or 24 hours (The BMJ), however timeframes cannot be guaranteed. Responses must comply with our requirements and should contribute substantially to the topic, but it is at our absolute discretion whether we publish a response, and we reserve the right to edit or remove responses before and after publication and also republish some or all in other BMJ publications, including third party local editions in other countries and languages
  • Our requirements are stated in our rapid response terms and conditions and must be read. These include ensuring that: i) you do not include any illustrative content including tables and graphs, ii) you do not include any information that includes specifics about any patients,iii) you do not include any original data, unless it has already been published in a peer reviewed journal and you have included a reference, iv) your response is lawful, not defamatory, original and accurate, v) you declare any competing interests, vi) you understand that your name and other personal details set out in our rapid response terms and conditions will be published with any responses we publish and vii) you understand that once a response is published, we may continue to publish your response and/or edit or remove it in the future.
  • By submitting this rapid response you are agreeing to our terms and conditions for rapid responses and understand that your personal data will be processed in accordance with those terms and our privacy notice.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Vertical Tabs

Other responses

Jump to comment:

  • Published on:
    Collaborative Efforts for Improving Statistical Practice of Ophthalmic Data
    • Gui-shuang Ying, Associate Professor University of Pennsylvania
    • Other Contributors:
      • Harrison G Zhang, Undergraduate Student

    We thank Dr. Bunce et al for their interest in our paper.1 We would like to apologize for not mentioning the Statistics Notes Series2-12 from the UK Ophthalmology Research Section of the NIHR Statistics group. Given that our paper’s purpose is to evaluate whether the correlated eye data were analyzed properly in published ophthalmic clinical science papers, we did not cite these papers because we think most of them serve as introductions of general statistical methods instead of specific statistical methods for correlated eye data.

    We agree these Statistics Notes Series are very helpful to the vision research community to improve the statistical analysis and interpretation of ophthalmic data. We applaud the UK Ophthalmology Research Section of the NIHR Statistics group for their collaborative efforts in improving the quality of statistics for ophthalmic research through these series of publications and workshops. Similarly in the USA, we have been promoting the proper analysis of correlated eye data through tutorial papers13-14 and the ARVO short course. We believe all these efforts will lead to improvement in the statistical practice for ophthalmic data.

    We also agree that there are varying degrees of misuse of statistical methods in analyzing correlated eye data. Ignoring the inter-eye correlation when data from both eyes are analyzed is very bad practice as it can lead to the invalid conclusion, while analyzing correlated ocular data at person-level does...

    Show More
    Conflict of Interest:
    None declared.
  • Published on:
    Better collaboration to optimise research
    • Catey Bunce, Reader in Medical Statistics King's College London
    • Other Contributors:
      • Irene Stratton, Senior Statistician
      • Ana Quartilho, Senior Statistician
      • Joanna Moschandreas, Senior Medical Statistician
      • John Lawrenson, Professor of Clinical Visual Science
      • Richard Wormald, Consultant Ophthalmologist
      • David Garway-Heath, Professor of Opthalmology for Glaucoma & Allied Studies

    We read with great interest the recent paper by Zhang and Ying exploring statistical approaches in published ophthalmic clinical science papers.1 We very much agree with the main conclusion drawn by the authors that collaborative efforts should be made in the vision research community to improve statistical practise for ocular data. In this vein, however, we were disappointed not to see reference to the Statistics Notes Series that has been published in this very journal. These have been written with a view to tackling some of the more prevalent statistical issues within ophthalmology and we would encourage readers to make use of these.2- 12. Within the UK this view that there needs to be greater collaboration in the vision research community has led to the formation of the Ophthalmology Research Section of the NIHR Statistics group which is championing cross- professional collaboration and active discussion in relation to statistical issues. It is always important when reviewing misuse of statistics in biomedical research to distinguish between misuse that leads to distorted or incorrect results and those methods which do not fully use data to maximum potential given that this loss of information might be viewed as unethical. In this regard we find the results from Zhang et al pleasing in that the proportion of papers which analysed at the level of the individual because of the nature of the observation rose from 15.2 % in 1995 to 50 % in 2017. A finding which is...

    Show More
    Conflict of Interest:
    None declared.