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Estimating structural equation models using James–Stein type shrinkage estimators

Elissa Burghgraeve (UGent) , Jan De Neve (UGent) and Yves Rosseel (UGent)
(2021) PSYCHOMETRIKA. 86(1). p.96-130
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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
Applied Mathematics, General Psychology, regression calibration, measurement error, shrinkage estimator

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MLA
Burghgraeve, Elissa, et al. “Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators.” PSYCHOMETRIKA, vol. 86, no. 1, 2021, pp. 96–130, doi:10.1007/s11336-021-09749-2.
APA
Burghgraeve, E., De Neve, J., & Rosseel, Y. (2021). Estimating structural equation models using James–Stein type shrinkage estimators. PSYCHOMETRIKA, 86(1), 96–130. https://doi.org/10.1007/s11336-021-09749-2
Chicago author-date
Burghgraeve, Elissa, Jan De Neve, and Yves Rosseel. 2021. “Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators.” PSYCHOMETRIKA 86 (1): 96–130. https://doi.org/10.1007/s11336-021-09749-2.
Chicago author-date (all authors)
Burghgraeve, Elissa, Jan De Neve, and Yves Rosseel. 2021. “Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators.” PSYCHOMETRIKA 86 (1): 96–130. doi:10.1007/s11336-021-09749-2.
Vancouver
1.
Burghgraeve E, De Neve J, Rosseel Y. Estimating structural equation models using James–Stein type shrinkage estimators. PSYCHOMETRIKA. 2021;86(1):96–130.
IEEE
[1]
E. Burghgraeve, J. De Neve, and Y. Rosseel, “Estimating structural equation models using James–Stein type shrinkage estimators,” PSYCHOMETRIKA, vol. 86, no. 1, pp. 96–130, 2021.
@article{8700512,
  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.}},
  author       = {{Burghgraeve, Elissa and De Neve, Jan and Rosseel, Yves}},
  issn         = {{0033-3123}},
  journal      = {{PSYCHOMETRIKA}},
  keywords     = {{Applied Mathematics,General Psychology,regression calibration,measurement error,shrinkage estimator}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{96--130}},
  title        = {{Estimating structural equation models using James–Stein type shrinkage estimators}},
  url          = {{http://dx.doi.org/10.1007/s11336-021-09749-2}},
  volume       = {{86}},
  year         = {{2021}},
}

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