Writing

How LLMs Are Changing Research

In this post I will discuss some of the ways that I currently see large language models influencing statistical analysis as well as ways that the same LLMs will influence analysis in the days and weeks to come!

Why Tetration Never Made It Into the Arithmetic Textbooks

Humans use the symbolic operators which are most convenient for them to express their most important curvilinear functions. Addition, multiplication, and exponentiation are common place; but higher order operators remain an esoteric topic. This short article explores some potential reasons why this might be.

A distribution that models the Dunning-Kruger effect: the tetration distribution

Iterated exponentiation on the unit interval produces exactly the non-linearity the DK calibration curve requires. Here is the formal model.

Adaptive trial designs: when flexibility helps and when it hurts

Adaptive designs can dramatically reduce sample size -- or introduce bias that sinks your results.

renv + targets: the reproducible R workflow I actually use

Two tools, properly configured, eliminate almost every 'it works on my machine' problem in R-based research.

Power calculations are not magic -- a guide for investigators

Most power calculations are optimistic by design. Here's how to pressure-test yours before the IRB does.

What to put in your statistical analysis plan (and what to leave out)

An SAP that's too vague gets you in trouble with reviewers. One that's too rigid ties your hands mid-study.

Building reproducible pipelines: the stack that doesn't break in six months

Most analysis code is write-once. Here's how to build workflows your team can maintain, audit, and extend.

When to use Bayesian vs. frequentist -- a practical guide for clinical researchers

The choice isn't philosophical. It depends on your prior information, regulatory context, and what you're trying to communicate.