Latent state-trait theory and research in personality and individual differences
Abstract
Latent state–trait (LST) theory is a generalization of classical test theory designed to take account of the fact that psychological measurement does not take place in a situational vacuum. The basic concepts of latent state–trait theory (LST theory) are introduced. The core of LST theory consists of two decompositions: (a) the decomposition of any observed score into latent state and measurement error, and (b) the decomposition of any latent state into latent trait and latent state residual representing situational and/or interaction effects. Latent states and latent traits are defined as special conditional expectations. A score on a latent state variable is defined as the expectation of an observable variable Yik given a person in a situation whereas a score on a latent trait variable is the expectation of Yik given a person. The theory also comprises the definition of consistency, occasion specificity, reliability, and stability coefficients. An overview of different models of LST theory is given. It is shown how different research questions of personality psychology can be and have been analysed within the LST framework and why research in personality and individual differences can profit from LST theory and methodology. Copyright © 1999 John Wiley & Sons, Ltd.
Cite this
Rolf Steyer, Manfred Schmitt, Michael Eid (1999). Latent state-trait theory and research in personality and individual differences. European Journal of Personality. https://doi.org/10.1002/(sici)1099-0984(199909/10)13:5<389::aid-per361>3.0.co;2-a
@article{rolf1999latent,
title = {Latent state-trait theory and research in personality and individual differences},
author = {Steyer, Rolf and Schmitt, Manfred and Eid, Michael},
year = {1999},
journal = {European Journal of Personality},
doi = {10.1002/(sici)1099-0984(199909/10)13:5<389::aid-per361>3.0.co;2-a}
}Citations in this library
Stored only when both papers are in the corpus — 508 citations exist upstream.