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Causal Assessment in Environmental Studies

  1. Susan B. Norton1,
  2. Glenn W. Suter II2

Published Online: 22 APR 2014

DOI: 10.1002/9781118445112.stat07669

Wiley StatsRef: Statistics Reference Online

Wiley StatsRef: Statistics Reference Online

How to Cite

Norton, S. B. and W. Suter, G. 2014. Causal Assessment in Environmental Studies . Wiley StatsRef: Statistics Reference Online. .

Author Information

  1. 1

    US Environmental Protection Agency, Washington, DC, USA

  2. 2

    US Environmental Protection Agency, Cincinnati, OH, USA

  1. This article was originally published online in 2006 in Encyclopedia of Environmetrics, © John Wiley & Sons, Ltd and republished in Wiley StatsRef: Statistics Reference Online, 2014.

Publication History

  1. Published Online: 22 APR 2014


Causal assessments bring together information to reach conclusions about how biological effects happened or can be produced. In environmental studies, a causal assessment may be prompted by observations of undesirable biological effects, concerns over a source or stressor, or questions about the efficacy of management actions. Observational studies are often the principal source of evidence available for causal assessments of environmental issues, but are problematic because causes are not manipulated, replicated, or randomly applied. Pragmatic strategies for interpreting observational study results for causal assessment include breaking up and analyzing causal pathways by mechanistic segment; comparing evidence for alternative causal explanations; using study design or statistical techniques to isolate the effects of individual variables; modeling the effects of multiple variables together; and supplementing observational results with evidence of sufficiency, exposure, and symptoms. Weight-of-evidence approaches are well suited to causal assessments because they can provide a common framework for synthesizing disparate types of information while retaining the evidence supporting or refuting conclusions.


  • causation;
  • causal assessment;
  • diagnosis;
  • weight-of-evidence;
  • observational studies;
  • confounding factors