Jonathan Rougier - Nomograms for visualising relationships between three variables (useR! 2011)

Background:

Example of Nomogram taken from wikipedia

Donkeys in Kenya. Tricky to find the weight of a donkey in the “field” – no pun intended! So using a few measurements,  estimate the weight. Other covariates include age. Standard practice is to fit:

for adult donkeys, and other slightly different models for young/old and ill donkeys. What can a statistician add:

• Add in other factors;
• Don’t (automatically) take logs of everything;
• Fit interactions.

Box-Cox suggested that a square-transformation could be a good transformation. Full model has age, health, height and girth. Final model is:

We want a simple way of using this model in the field. Use a monogram!

Digression on nomograms

Nomograms are visual tools for representing the relationship between three or more variables. Variations include:

• curved scaled nomograms;
• some others that I missed.

Lots of very nice nomograms from “The lost art of Nomograms”.

Back to donkeys

If we used a log transformation for weight rather than square root we get slightly higher weights for smaller/larger donkeys. Nomograms nicely highlight this.

Summary

Nomograms can be clearer and simpler, but don’t display predictive uncertainty.

References:

• pynomo for creating nomograms.
• R. Doerfler, “The Lost Art of Nomography,” The UMAP Journal 30(4), 2009 pp. 457–493.
• Ron’s site and blog