{
  "abstract": "Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors persist across various disciplines. With a background in biostatistics and over 200 articles reviewed for journals such as Heart and Addiction since 2021, two differing and distinct research areas, I (DJG) have identified 10 common statistical mistakes that authors frequently make. Together with two academic colleagues, we present these issues in a concise, direct and accessible way to help researchers avoid them. This article will not repeat the pitfalls documented previously; rather, it reflects independent observations on statistical and presentational issues frequently made by authors across various medical fields.",
  "authors": [
    {
      "affiliations": [
        "School of Optometry, College of Health and Life Sciences, Aston University, Birmingham, UK"
      ],
      "name": "Dan J Green"
    },
    {
      "affiliations": [
        "Riverside Innovation Centre, FUZE, Chester, UK"
      ],
      "name": "Diane Smith"
    },
    {
      "affiliations": [
        "Department of Applied Health Sciences, University of Birmingham, Birmingham, UK",
        "National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK"
      ],
      "name": "Rebecca Whittle"
    }
  ],
  "title": "Top 10 statistical pitfalls: a reviewer’s guide to avoiding common errors",
  "uid": "e2729496-2235-5b4e-b7b1-e2bc2f926a8d"
}