An alternative two stage least squares (2SLS) estimator for latent variable equations

被引:230
作者
Bollen, KA
机构
[1] CB 3210 Hamilton, Department of Sociology, University of North Carolina, Chapel Hill
关键词
structural equation models; covariance structure models; LISREL; two stage least squares; 2SLS; latent variables; factor analysis; noniterative estimators; instrumental variables;
D O I
10.1007/BF02296961
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Maximum-likelihood estimator dominates the estimation of general structural equation models. Noniterative, equation-by-equation estimators for factor analysis have received some attention, but little has been done on such estimators for latent variable equations. I propose an alternative 2SLS estimator of the parameters in LISREL type models and contrast it with the existing ones. The new 2SLS estimator allows observed and latent variables to originate from nonnormal distributions, is consistent, has a known asymptotic covariance matrix, and is estimable with standard statistical software. Diagnostics for evaluating instrumental variables are described. An empirical example illustrates the estimator.
引用
收藏
页码:109 / 121
页数:13
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