Problems in the measurement of latent variables in structural equations causal models

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Problems in the measurement of latent variables in structural equations causal models

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1990

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Some problems in the measurement of latent variables in structural equations causal models are presented, with examples from recent empirical studies. Latent variables that are theoretically the source of correlation among the empirical indicators are differentiated from unmeasured variables that are related to the empirical indicators for other reasons. It is pointed out that these should also be represented by different analytical models, and that much published research has treated this distinction as if it had no analytic consequences. The connection between this theoretical distinction and disattenuation effects in latent variable models is shown, and problems with these estimates are discussed. Finally, recommendations are made for decisions about whether and how to measure latent variables when manifest variables are potentially available. Index terms: causal models, disattenuation, emergent variables, latent variable measurement, latent variables, structural equations modeling.

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De Gruijter, Dato N. (1990). Test construction by means of linear programming. Applied Psychological Measurement, 14, 175-181. doi:10.1177/014662169001400206

Suggested citation

Cohen, Patricia; Cohen, Jacob; Teresi, Jeanne; Marchi, Margaret L.; Velez, C. Noemi. (1990). Problems in the measurement of latent variables in structural equations causal models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/113260.

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