Factor Analyses (FA) are a set of techniques that allows us to look in more detail at the strength of underlying correlations between scores on the items of a measure. These provide some useful indication about whether items appear to tap common, i.e. shared, sources of variation between individuals, a major part of construct validity. Historically FA was exploratory: Exploratory Factor Analysis (EFA), actually often a closely related approach called Principal Component Analysis (PCA) or, less often, Multi-Dimensional Scaling (MDS). More recently, with much more computer power avialable, Confirmatory Factor Analysis (CFA), which can test an expected mapping of items to presumed factors has become fashionable. |
Detail #
See Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA) for more detail, Construct Validity for background detail. Principal Component Analysis (PCA) and Multi-Dimensional Scaling (MDS) are background, not central to FA.
Try also … #
Confirmatory Factor Analysis (CFA)
Exploratory Factor Analysis (EFA)
Principal Component Analysis (PCA)
Construct Validity
Multi-Dimensional Scaling (MDS).
Chapters #
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Further reading #
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Online applications #
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