Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators

Elissa Burghgraeve (), Jan De Neve and Yves Rosseel
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Elissa Burghgraeve: GHENT UNIVERSITY
Jan De Neve: GHENT UNIVERSITY
Yves Rosseel: GHENT UNIVERSITY

Psychometrika, 2021, vol. 86, issue 1, No 4, 96-130

Abstract: Abstract We propose a two-step procedure to estimate structural equation models (SEMs). In a first step, the latent variable is replaced by its conditional expectation given the observed data. This conditional expectation is estimated using a James–Stein type shrinkage estimator. The second step consists of regressing the dependent variables on this shrinkage estimator. In addition to linear SEMs, we also derive shrinkage estimators to estimate polynomials. We empirically demonstrate the feasibility of the proposed method via simulation and contrast the proposed estimator with ML and MIIV estimators under a limited number of simulation scenarios. We illustrate the method on a case study.

Keywords: regression calibration; measurement error; shrinkage estimator (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11336-021-09749-2

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