Causal diagrams and change variables

Eyal Shahar, Doron J. Shahar

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)143-148
Number of pages6
JournalJournal of Evaluation in Clinical Practice
Volume18
Issue number1
DOIs
Publication statusPublished - Feb 2012

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Keywords

  • Causal diagrams
  • Change score
  • Change variables
  • Directed acyclic graphs

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health Policy

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