Causal diagrams and change variables
1Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA. shahar@email.arizona.edu
Background:
The true change in the value of a variable between two time points is often assumed to be a cause or an effect of interest. To our knowledge, this assumption is based on intuition, rather than on any formal theoretical justification.
Methods:
We used causal directed acyclic graphs to explore the causal properties of a change variable, and critically examined competing structures.
Results:
Based on the proposed causal structure, a change variable (true change) is no more than a derived variable. It does not cause anything and is not of causal interest.
Conclusions:
A true change is not a variable in the physical world. Therefore, modelling the change between two time points is justified only in a few situations.
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