The issue of indeterminacy in the factor analysis model has been the source of a lengthy and on-going debate. This debate can be seen as featuring two relevant interpretations of indeterminacy. The alternative solution position considers the latent common factor to be a random variate whose properties are determined by functional constraints inherent in the model. When the model fits the data, an infinity of random variates are criterially latent common factors to the set of manifest variates analyzed. The posterior moment position considers the latent common factor to be a single random entity with a non-point posterior distribution, given the manifest variables. It is argued here that: (a) The issue of indeterminacy centres on the criterion for the claim "X is a latent common factor to Y"; (b) the alternative solution position is correct, the posterior moment position representing a conflation of the criterion, which is provided by the equations of the model, with metaphors, analogies, and senses of "factor" that are external to the model. A number of implications for applied work involving factor analysis are discussed.

The authors argue that the current state of applied data-based test analytic practice is unstructured and unmethodical due in large part to the fact that there is no clearly specified, widely accepted test analytic framework for judging the performances of particular tests in particular contexts. Drawing from the extant test theory literature, they propose a rationale that may be used in data-based test analysis. The components of the proposed test analytic framework are outlined in detail, as are examples of the framework as applied to commonly encountered test evaluative scenarios. A number of potential extensions of the framework are discussed.

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Past research has documented myriad pernicious psychological effects of high economic inequality, prompting interest into how people perceive, evaluate, and react to inequality. Here we propose, refine, and validate the Support for Economic Inequality Scale (SEIS)–a novel measure of attitudes towards economic inequality. In Study 1, we distill eighteen items down to five, providing evidence for unidimensionality and reliability. In Study 2, we replicate the scale’s unidimensionality and reliability and demonstrate its validity. In Study 3, we evaluate a United States version of the SEIS. Finally, in Studies 4–5, we demonstrate the SEIS’s convergent and predictive validity, as well as evidence for the SEIS being distinct from other conceptually similar measures. The SEIS is a valid and reliable instrument for assessing perceptions of and reactions to economic inequality and provides a useful tool for researchers investigating the psychological underpinnings of economic inequality.

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