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In psychometrics, content validity (also known as logical validity) refers to the extent to which a measure represents all facets of a given social concept. For example, a depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension. An element of subjectivity exists in relation to determining content validity, which requires a degree of agreement about what a particular personality trait such as extroversion represents. A disagreement about a personality trait will prevent the gain of a high content validity.^[1]

Content validity is related to face validity, though content validity should not be confused with face validity. The latter is not validity in the technical sense; it refers, not to what the test actually measures, but to what it appears superficially to measure. Face validity pertains to whether the test "looks valid" to the examinees who take it, the administrative personnel who decide on its use, and other technically untrained observers. Content validity requires more rigorous statistical tests than face validity, which only requires an intuitive judgement. Content validity is most often addressed in academic and vocational testing, where test items need to reflect the knowledge actually required for a given topic area (e.g., history) or job skill (e.g., accounting). In clinical settings, content validity refers to the correspondence between test items and the symptom content of a syndrome.

One widely used method of measuring content validity was developed by C. H. Lawshe. It is essentially a method for gauging agreement among raters or judges regarding how essential a particular item is. Lawshe (1975) proposed that each raters on the judging panel respond to the following question for each item: "Is the skill or knowledge measured by this item essential/useful but not essential/ not necessary to the performance of the construct?" According to Lawshe, if more than half the panelists indicate that an item is essential, that item has at least some content validity. Greater level of content validity exist as larger numbers of panelists agree that a particular item is essential. Using these assumptions, Lawshe developed a formula termed the content validity ratio:

                            CVR = (ne - N/2)/(N/2)

CVR= content validity ratio, n_e= number of panelists indicating "essential", N= total number of panelists. And the minimum values of the CVR to ensure that agreement is unlikely to be due to chance can be found in the following table:

• Validity (statistics)

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