Blog Posts

Large P-Values Cannot be Explained by Power Analysis

Can p-values be close to .05 because researchers ran careful power analysis, and collected ‘just enough’ participants to detect their effect? In this blog post, I evaluate the merits of this argument.

A Bad Pre-Registration is Better than No Pre-Registration

A short blog post showing the immense benefits of pre-registration on false-positive rates, even when the pre-registration is underspecified.

A Critical Perspective on Effect Sizes

What can we learn from effect sizes, and under which conditions?

Making Discussions of Statistical Evidence Less Awkward and More Constructive

How can researchers respectfully and constructively flag inadequate statistical evidence when we they see it in papers? This post offers some personal reflections on this complex question.

Evaluating the Strength of Statistical Evidence Presented in a Paper

A primer on evaluating statistical evidence, with a focus on p-curve analysis.

Cleaning and Analyzing distBuilder Data in R

You have used the distBuilder library to collect data, now what? This post walks you through the basics of cleaning and analyzing distribution builder data in R.

Adding Totals to distBuilder

A short tutorial on adding “totals” to distBuilder, keeping track of how many balls are allocated in each bucket

Correctly Dealing with Outliers (Part Two)

A two-part blog post on outlier exclusion procedures, and their impact on false-positive rates.

Correctly Dealing with Outliers (Part One)

A two-part blog post on outlier exclusion procedures, and their impact on false-positive rates.

How Not To Deal with Outliers

A short case study showing how not to deal with your outliers, featuring a recent paper published in psychology.