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Factor analysis is used extensively in the construction of psychometric scales. It may appear to be a mathematically precise and objective technique, but it involves many subjective choices and its results require subjective interpretation. Factor interpretations are hypotheses that
should be tested, yet often are accepted simply on the basis of post hoc expert judgment. Untested judgments about the meaning of factors sometimes result in mislabeling of published scales and misinterpretation of research findings. This article cites several such cases to illustrate the
need for testing factor-interpretation hypotheses and the difficulty of doing so without bias. Techniques for generating and testing such hypotheses are then reviewed.