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Construct validity concerns how well a set of indicators represent or reflect a concept that is not directly measurable. [1][2][3] Construct validation is the accumulation of evidence to support the interpretation of what a measure reflects. [1][4][5][6] Modern validity theory defines construct validity as the overarching concern of validity ...
Multitrait-multimethod matrix. The multitrait-multimethod (MTMM) matrix is an approach to examining construct validity developed by Campbell and Fiske (1959). [1] It organizes convergent and discriminant validity evidence for comparison of how a measure relates to other measures. The conceptual approach has influenced experimental design and ...
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
Confirmatory factor analysis. In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social science research. [1] It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor).
Concurrent validity is a type of evidence that can be gathered to defend the use of a test for predicting other outcomes. It is a parameter used in sociology, psychology, and other psychometric or behavioral sciences. Concurrent validity is demonstrated when a test correlates well with a measure that has previously been validated.
Convergent validity. Convergent validity in the behavioral sciences refers to the degree to which two measures that theoretically should be related, are in fact related. [1] Convergent validity, along with discriminant validity, is a subtype of construct validity. Convergent validity can be established if two similar constructs correspond with ...
In statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model. To combat this, model validation is ...
There are a lack of studies that support the construct validity of the CD-RISC. In order for a measure to demonstrate good construct validity, it needs to be based on a complex, detailed theoretical construct (i.e., nomological network). If the measure has good construct validity, then it should "behave" as a measure of this complex concept ...