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.
De Gruijter, Dato N. (1990). Test construction by means of linear programming. Applied Psychological Measurement, 14, 175-181. doi:10.1177/014662169001400206
Cohen, Patricia; Cohen, Jacob; Teresi, Jeanne; Marchi, Margaret L.; Velez, C. Noemi.
Problems in the measurement of latent variables in structural equations causal models.
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