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Criterion validity

As explained in Effective Data Analysis

Criterion validity is the degree to which a measure is associated with an external criterion representing an established measure or outcome of interest.

Criterion validity is the degree to which a measure is associated with an established measure or outcome representing the phenomenon of interest. It helps establish whether a measurement supports meaningful, trustworthy conclusions. section 6.3.2 section 6.4

Use criterion validity alongside content or face validity and construct validity. Together, these checks ask whether a measure covers the relevant facets, represents the intended theoretical construct, and aligns with related measures. section 6.3.2 section 6.4

A practical validity review should:

  • Identify the concept or process the measure is intended to capture. section 6.3.2
  • Compare the measure with an established measure or outcome that represents the same or a similar construct. section 6.4
  • Use the resulting evidence to build stakeholder confidence that findings reflect the phenomenon being investigated. section 6.3.2

How Effective Data Analysis covers it

How deep it goes
Defines an association-based validity check but does not specify statistical procedures, thresholds, or worked calculations.
What it assumes
Assumes a defined concept and measure, and follows initial confidence that the measure is reliable.
What you can do after
Evaluate whether a measure corresponds with related measures or outcomes before using its results to support decisions.
How it connects
Connects validity with content or face validity, construct validity, reliability, and stakeholder decision-making.
Cover of Effective Data Analysis
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.