Validity
#researchlandscape
Different types of validity: Face Content Criterion Construct Internal External Concurrent Predictive Convergent Discriminant Ecological Statistical Conclusion Validity.
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Face Validity: It is an estimate of whether a test appears to measure a certain criterion. It does not guarantee that the test actually measures phenomena in that domain.
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Content Validity: It refers to the extent to which a measure represents all facets of a given construct.
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Criterion Validity: It is the extent to which one measure predicts an outcome for another measure.
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Construct Validity: It refers to the degree to which a test measures what it claims, or purports, to be measuring.
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Internal Validity: It reflects how well an experiment is done, especially whether it avoids confounding (more than one possible independent variable [cause] acting at the same time).
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External Validity: This type of validity relates to how well the outcome of a study can be expected to apply to other settings.
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Concurrent Validity: This type of validity measures a test against a benchmark test and high correlation indicates that the test has strong criterion validity.
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Predictive Validity: This is when the criterion measures are obtained at a time after the test.
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Convergent Validity: This type of validity takes two measures that are supposed to be measuring the same construct and shows that they are related.
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Discriminant Validity: Tests whether concepts or measurements that are supposed to be unrelated are, in fact, unrelated.
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Ecological Validity: The extent to which research findings can be generalized from the setting in which they were obtained (the laboratory) to real-world settings (outdoors).
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Statistical Conclusion Validity: The degree to which conclusions about the relationship among variables based on data are correct or ‘reasonable’.
Related to reliability