ESTIMATOR TWO STAGE LEAST SQUARES (2SLS) PADA MODEL PERSAMAAN STRUKTURAL DENGAN VARIABEL LATEN; ( TWO STAGE LEAST SQUARES (2SLS) ESTIMATOR IN STRUCTURAL EQUATION MODEL WITH LATENT VARIABLE

MIFTAHULKHAIRAH, Abdurakhman

2014 | Disertasi | PROGRAM STUDI S2 MATEMATIKA

Structural Equation Model (SEM) with latent variable is a powerful tool for social and behavioral scientists, because it combines a lot of psychometrics and econometrics into a single framework. The estimator often used in SEM is Maximum Likelihood Estimator (MLE). When the high properties desired, the MLE and the other full information estimators will otherwise remain lacked. The main thing is that when a part of the model misspecified, almost always the case. The bias can be spread on the specific model, because the model parameter estimation is conducted simultaneously. With these reasons, the optional alternative study is continuous limited information estimator; Two Stage Least Squares (2SLS) estimator. It can be used on a small sample and does not require the assumption of distribution for the independent variables on the right side, so it can be applied to non-normal or binary data. In addition, in the context of multi non-recursive equation, 2SLS estimator is able to isolate specific errors for a single equation, including simple computing and it does not require the use of numeric optimization algorithms. In this study expound the steps 2SLS estimator and its application in the SEM with latent variable.

Kata Kunci : 2SLS; SEM; Variabel Laten