Known-groups validity is used to assess construct validity by...

Known-groups validity is used to assess construct validity by...

• A. It compares groups known to differ on the construct to see if the measure can distinguish them.
• B. It tests the consistency of a measure across time.
• C. It uses factor analysis to validate the structure.
• D. It assesses internal consistency.

Answer: (A)

Known-groups validity looks at whether a measure can distinguish between groups that are known to differ on the underlying construct. If the instrument truly taps that construct, you should see higher (or lower) scores for the group expected to differ, matching theoretical predictions. This provides evidence that the measure is sensitive to real differences related to the construct, supporting construct validity. For example, a mood or anxiety scale should yield higher scores for individuals experiencing anxiety symptoms than for those without such symptoms, reflecting that the instrument is capturing the intended construct rather than random variation. Why the other options don’t fit here: testing consistency across time is about reliability (test-retest), not validity. Using factor analysis is about validating the structure or dimensionality of the measure, which is a different aspect of validity. Assessing internal consistency is also a reliability property, focusing on how well items within a scale hang together, not whether the measure differentiates groups as theory would predict.

Known-groups validity looks at whether a measure can distinguish between groups that are known to differ on the underlying construct. If the instrument truly taps that construct, you should see higher (or lower) scores for the group expected to differ, matching theoretical predictions. This provides evidence that the measure is sensitive to real differences related to the construct, supporting construct validity.

For example, a mood or anxiety scale should yield higher scores for individuals experiencing anxiety symptoms than for those without such symptoms, reflecting that the instrument is capturing the intended construct rather than random variation.

Why the other options don’t fit here: testing consistency across time is about reliability (test-retest), not validity. Using factor analysis is about validating the structure or dimensionality of the measure, which is a different aspect of validity. Assessing internal consistency is also a reliability property, focusing on how well items within a scale hang together, not whether the measure differentiates groups as theory would predict.