A simulation of a two-group parallel-arm randomized trial with interim analysis using the rpact package.

This post goes through the R code and logic that was used to construct the figures and concepts in Rafi & Greenland (2020) BMC MRM.

Sensitivity analyses are an important part of statistical analyses, however, there are major misconceptions about what they do and what qualifies as such an analysis.

Experienced statisticians and data analysts are familiar with stories where a coding error has led to an entire conclusion changing, even leading to a retraction. It's the sort of stuff that keeps people up at night.

An early look at Gelman et als new book, Regression and Other Stories, which is an update to their seminal 2006 book, Data Analysis Using Regression and Multilevel Hierarchical Models.

A review of Erich Lehmann's last book, Fisher, Neyman, and the Creation of Classical Statistics.

An extensive discussion about what P-values are, their properties, common interpretations, misinterpretations, and how a measure called an S-value may better help us interpret them.

Discussions praising the efficiency of randomized trials are widespread, however, few of these discussions take a close look at some of the common assumptions that individuals hold regarding randomized trials. And unfortunately, these common assumptions may be based on outdated evidence and simplistic ideas.

Another misinterpretation of what statistical power is and how trial results should be reported in a popular journal.

The Bradford Hill viewpoints are commonly used as a checklist to argue for causality when randomized trials aren't possible. However, the originator of these viewpoints never intended for them to be used this way. In this post, I examine the shortcomings of using these viewpoints as a checklist in the real world.