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|Title:||Limited information estimators||Authors:||JIA JIAOYANG||Keywords:||limited information estimator, two-stage least square estimator, heteroskedasticity, factor analysis model||Issue Date:||15-Dec-2003||Citation:||JIA JIAOYANG (2003-12-15). Limited information estimators. ScholarBank@NUS Repository.||Abstract:||In this thesis, we examine several versions of the heteroskedasticity-consistent covariance matrix estimators for the factor analysis model. These estimators are extensions of Hinkley (1977), White (1980), Shao and Wu (1987) and Cribari-Neto (2000) that were proposed for the ordinary least squares estimators in the classical linear regression model. We consider the two-stage least squares estimation method and present versions of these heteroskedasticity-consistent covariance matrix estimators for the factor loadings in the factor analysis model. A simulation study was conducted to assess and compare these variance estimators, under different factor and error distributions.||URI:||http://scholarbank.nus.edu.sg/handle/10635/13526|
|Appears in Collections:||Master's Theses (Open)|
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