Visualization

13 posts

• Why Adjusted Regression Coefficients Are Less Descriptive Than They Look

  Jun 25, 2026 · 10 min read · Statistics

  An interactive article about how regression adjustment works and the pitfalls of conditional associations in descriptive studies.

• Introducing PowerLMM.js: Browser-based power analysis for longitudinal models with dropout

  Dec 11, 2024 · 1 min read · Statistics

  A new tool for power analysis of longitudinal linear mixed-effects models (LMMs), with support for missing data, random slopes, and non-inferiority and equivalence tests.

• The Cohen's d app translation project

  Oct 29, 2022 · 1 min read · Visualization

  My Cohen's d app supports multiple languages, and any help translating the content into more languages is very welcome.

• New d3.js visualization: Equivalence, non-inferiority and superiority testing

  Nov 29, 2016 · 1 min read · D3.js

  This visualization illustrates the appropriate tests to use when your research hypothesis is that two treatments are equally effective, or that a new treatment is no worse than the current gold standard.

• New d3.js visualization: Bayesian inference

  Nov 22, 2015 · 1 min read · D3.js

  The visualization illustrates a Bayesian two-sample t test

• [Updated] Statistical Power and Significance Testing Visualization

  Aug 24, 2015 · 1 min read · D3.js

  I've added more options to my NHST visualization

• [Update] P-curve visualization updated with log x-axis

  Aug 13, 2015 · 1 min read · D3.js

  My p-curve visualization has been updated with the option to log the x-axis.

• New d3.js visualization: the t-distribution and its normal approximation

  Jun 8, 2015 · 1 min read · D3.js

  This visualization shows how the t-distribution and the Gaussian (normal) distribution approaches each other when sample size increases.

• New visualization of the distribution of p-values using d3.js

  Mar 21, 2015 · 1 min read · D3.js

  Here's a new visualization that shows the p-curve distribution when comparing the means of two independent samples for varying effects. Many know that the distribution is uniform when the null is true, but what about when it isn't?

• Interpreting Confidence Intervals – new d3.js visualization

  Nov 28, 2014 · 1 min read · D3.js

  Understand confidence intervals by using my new interactive visualization.

• New d3.js visualization: Interpreting Correlations

  Aug 1, 2014 · 1 min read · D3.js

  This new visualization is an interactive display of the correlation between two variables.

• New d3.js visualization: Understanding Significance Testing and Statistical Power

  Feb 2, 2014 · 1 min read · D3.js

  This new visualization is an interactive display of classical null hypothesis significance testing and statistical power.

• New d3.js visualization: Interpreting Cohen’s d effect size

  Jan 13, 2014 · 1 min read · D3.js

  I have created a new visualization in D3. The purpose is to aid in the interpretation of Cohen’s d.