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When defining evaluation criteria with constructed scales, it
is often desirable to define discrete levels or categories of
impact. These can be qualitative (low, medium, high) or
quantitative (0-20 hectares, 20-50 hectares, etc.).
Many assumptions may go into the assignment of these impact
levels. Inference trees document explanatory factors used in
making an assessment of an impact level, along with the
supporting data used. It is a useful format for documenting
layers of causal factors that are considered in making
judgments. A disadvantage is that this approach lacks a means to
represent interactions among causal factors, or a system for
quantifying relationships among the factors.
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Inference trees add rigor and transparency when
assigning values to complex constructed scales