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Construct validity

As explained in Effective Data Analysis

Construct validity is the degree to which a measure accurately assesses the theoretical construct it is intended to measure and exhibits theoretically expected relationships.

Construct validity is the degree to which a measure accurately assesses the theoretical construct it is intended to measure. It asks whether the operational measure represents the intended concept rather than a related or unintended phenomenon. section 6.3.2 section 6.4

Assess construct validity after establishing that measures are reliable, and use it to support meaningful, trustworthy results for stakeholder decisions. Distinguish it from content or face validity, which examines coverage of a concept, and criterion validity, which examines association with similar measures. section 6.3.2 section 6.4

Use these questions when evaluating a measure:

  • Does the measure correspond to the theoretical construct it claims to represent? section 6.3.2
  • Does it produce results that reflect the phenomenon being investigated and justify stakeholder confidence? section 6.4

How Effective Data Analysis covers it

How deep it goes
Defines the theoretical measurement target and distinguishes related validity types, but supplies no detailed construct-validation procedure.
Examples
Uses employee job satisfaction to illustrate conceptualizing a measure and covering its relevant facets.
What it assumes
Assumes a defined theoretical concept and prior attention to measurement reliability.
What you can do after
Evaluate whether a measure captures its intended construct and supports meaningful, trustworthy stakeholder decisions.
How it connects
Connects construct validity with reliability, content or face validity, criterion validity, and internal consistency.
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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.