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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). As such, the objective of confirmatory factor analysis is to ...
Intervention studies where a group with low scores in the construct is tested, taught the construct, and then re-measured can demonstrate a test's construct validity. If there is a significant difference pre-test and post-test, which are analyzed by statistical tests, then this may demonstrate good construct validity.
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables.
Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms hypothetical variables or hypothetical constructs may be used in these situations. The use of latent variables can serve to reduce the dimensionality of data. Many observable variables can be aggregated in a model ...
The average variance extracted has often been used to assess discriminant validity based on the following "rule of thumb": the positive square root of the AVE for each of the latent variables should be higher than the highest correlation with any other latent variable. If that is the case, discriminant validity is established at the construct ...
In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [ 1 ]
Measurement invariance or measurement equivalence is a statistical property of measurement that indicates that the same construct is being measured across some specified groups. [1] For example, measurement invariance can be used to study whether a given measure is interpreted in a conceptually similar manner by respondents representing ...
Validity evidence based on nomological validity is a general form of construct validity. It is the degree to which a construct behaves as it should within a system of related constructs (the nomological network). [3] Nomological networks are used in theory development and use a modernist [clarification needed] approach. [4]