How to get your article rejected by the BMJ: 12 common statistical issues

Medical research is full of statistical issues and pitfalls, and many articles are rejected due to statistical concerns. As a Prof of Biostatistics & also a Statistics Editor for the BMJ, I see this every day. Here, I outline 12 common problems in the hope that flagging these will raise awareness and improve research quality in the future. Intended for a broad audience, the talk is based on our BMJ article "On the 12th day of Christmas, a statistician sent to me" published in 2022 (https://www.bmj.com/content/379/bmj-2...) - for a one-page summary see image here   / 1612396496443301889   Enjoy! Hope this helps you in your research.

Join Today
Clinical Prediction Models & The Multiverse of Madness
▶︎

Clinical Prediction Models & The Multiverse of Madness

Importance of sample size for AI-based prediction models in healthcare
▶︎

Importance of sample size for AI-based prediction models in healthcare

Method Performance Criteria in Quantitative Chemical Analysis in Environment, HBM and Food
▶︎

Method Performance Criteria in Quantitative Chemical Analysis in Environment, HBM and Food

Frequentism and Bayesianism: What's the Big Deal? | SciPy 2014 | Jake VanderPlas
▶︎

Frequentism and Bayesianism: What's the Big Deal? | SciPy 2014 | Jake VanderPlas

SQL Course for Beginners [Full Course]
▶︎

SQL Course for Beginners [Full Course]

Chronic Headaches: OSA or mTBI?
▶︎

Chronic Headaches: OSA or mTBI?

Andrew Gelman - Wrong Again! 30+ Years of Statistical Mistakes
▶︎

Andrew Gelman - Wrong Again! 30+ Years of Statistical Mistakes

Individual Participant Data (IPD) meta-analysis: advanced topics & recent debates
▶︎

Individual Participant Data (IPD) meta-analysis: advanced topics & recent debates

Introduction To Causal Inference And Directed Acyclic Graphs
▶︎

Introduction To Causal Inference And Directed Acyclic Graphs

A general sample size framework for developing or updating a predictive algorithm (prediction model)
▶︎

A general sample size framework for developing or updating a predictive algorithm (prediction model)

Statistics - A Full Lecture to learn Data Science (2025 Version)
▶︎

Statistics - A Full Lecture to learn Data Science (2025 Version)

Key Steps and Common Pitfalls in Clinical Prediction Model Research
▶︎

Key Steps and Common Pitfalls in Clinical Prediction Model Research

Intro to the Tidyverse
▶︎

Intro to the Tidyverse

Systematic Reviews of Prognosis Research & Prediction Models
▶︎

Systematic Reviews of Prognosis Research & Prediction Models

SBE CCC: Using weights when analyzing survey data: Descriptive Statistics vs. Regression Modeling
▶︎

SBE CCC: Using weights when analyzing survey data: Descriptive Statistics vs. Regression Modeling

Power Calculations for Individual Participant Data (IPD) Meta-Analysis Projects
▶︎

Power Calculations for Individual Participant Data (IPD) Meta-Analysis Projects

Regression Output Explained
▶︎

Regression Output Explained

How to interpret clinical trial data – Examples from recent clinical trials
▶︎

How to interpret clinical trial data – Examples from recent clinical trials

Stability of Clinical Prediction Models Developed Using Statistical or Machine Learning Approaches
▶︎

Stability of Clinical Prediction Models Developed Using Statistical or Machine Learning Approaches

Bad Statistics in Medical Research Prof Adrian Barnett
▶︎

Bad Statistics in Medical Research Prof Adrian Barnett