Blog and insights

Short, practical notes on statistical methods and research practice, written for researchers rather than statisticians.

About this blog

The JH Stat blog covers applied statistics, health research methods, responsible use of AI in health research and reproducible analysis.

The first article is published below. The remaining cards are planned topics, shown to indicate the kind of writing this section will contain — they are clearly marked and cannot yet be read.

If you would like to be told when new articles are published, or if there is a topic you would find useful, get in touch.

Planned categories

Writing will be organised under the following headings.

  • Applied statistics
  • Health research methods
  • Responsible AI in health research
  • Statistical reporting
  • Reproducible research

Articles

Articles and topics in preparation

Published articles can be read in full. Cards marked in preparation have not been written yet.

In preparation — not yet written
Health research methods Planned article

Why complete-case analysis is rarely the right default

Dropping incomplete records is the most common way missing data are handled, and usually the least defensible. This piece will set out the mechanisms behind missingness and what changes when multiple imputation is used instead.

Not yet published

In preparation — not yet written
Responsible AI in health research Planned article

When machine learning beats regression — and when it does not

Prediction models in health research are increasingly built with machine learning methods. This piece will look at where that genuinely improves performance, where a well-specified regression does just as well, and why calibration matters more than discrimination for clinical use.

Not yet published

Have a question that deserves an article?

If there is a statistical problem your team keeps running into, it is probably worth writing about. Suggestions are welcome — and if you need an answer sooner than the blog can provide one, ask directly.