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