Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators
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...
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| Veröffentlicht in: | Psychometrika 2021-03, Vol.86 (1), p.96-130 |
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| container_title | Psychometrika |
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| creator | Burghgraeve, Elissa De Neve, Jan Rosseel, Yves |
| description | 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. |
| doi_str_mv | 10.1007/s11336-021-09749-2 |
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| source | Education Source (EBSCOhost); SpringerLink Journals |
| subjects | Assessment Behavioral Science and Psychology Humanities Law Psychology Psychometrics Regression analysis Simulation Statistical Theory and Methods Statistics for Social Sciences Structural equation modeling Testing and Evaluation Theory and Methods Variables |
| title | Estimating Structural Equation Models Using James–Stein Type Shrinkage Estimators |
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