Model-implied instrumental variable-generalized method of moments (MIIV-GMM) estimators for latent variable models.
Model-implied instrumental variable-generalized method of moments (MIIV-GMM) estimators for latent variable models.
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DOI:
10.1007/s11336-013-9335-3
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发表时间:
2014-01
期刊:
影响因子:
3
通讯作者:
Bauldry S
中科院分区:
文献类型:
--
作者:
Bollen KA;Kolenikov S;Bauldry S
The common Maximum Likelihood (ML) estimator for structural equation models (SEMs) has optimal asymptotic properties under ideal conditions (e.g., correct structure, no excess kurtosis, etc.) that are rarely met in practice. This paper proposes Model Implied Instrumental Variable - Generalized Method of Moments (MIIV-GMM) estimators for latent variable SEMs that are more robust than ML to violations of both the model structure and distributional assumptions. Under less demanding assumptions the MIIV-GMM estimators are consistent, asymptotically unbiased, asymptotically normal, and have an asymptotic covariance matrix. They are “distribution-free”, robust to heteroscedasticity, and have overidentification goodness of fit J tests with asymptotic chi square distributions. In addition, MIIV-GMM estimators are “scalable” in that they can estimate and test the full model or any subset of equations and hence allow better pinpointing of those parts of the model that fit and do not fit the data. An empirical example illustrates MIIV-GMM estimators. A simulation study explores their finite sample properties and finds that they perform well across a range of sample sizes.
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DOI:
10.1016/0378-3758(78)90026-5
发表时间:
1978-01-01
影响因子:
0.9
作者:
GODAMBE, VP;THOMPSON, ME
通讯作者:
THOMPSON, ME
影响因子:
6.1
作者:
BENTLER, PM
通讯作者:
BENTLER, PM
DOI:
10.1146/annurev-soc-081309-150141
发表时间:
2012-01-01
期刊:
ANNUAL REVIEW OF SOCIOLOGY, VOL 38
影响因子:
--
作者:
Bollen, Kenneth A.
通讯作者:
Bollen, Kenneth A.
影响因子:
6.3
作者:
BOLLEN, KA;STINE, RA
通讯作者:
STINE, RA
影响因子:
2.5
作者:
Foster, EM
通讯作者:
Foster, EM