Abstract
The fixed effect meta-analytic structural equation modeling (MASEM) model assumes that the population effect is homogeneous across studies. It was first developed analytically using Generalized Least Squares (GLS) and computationally using Weighted Least Square (WLS) methods. The MASEM fixed effect was not estimated analytically using the estimation method based on moment. One of the classic estimation methods based on moment is the Generalized Method of Moments (GMM), whereas GMM can possibly estimate the data whose studies has parameter uncertainty problems, it also has a high accuracy on data heterogeneity. Therefore, this study estimates the fixed effect MASEM model using GMM. The symmetry of this research is based on the proof goodness of the estimator and the performance that it is analytical and numerical. The estimation results were proven to be the goodness of the estimator, unbiased and consistent. To show the performance of the obtained estimator, a comparison was carried out on the same data as the MASEM using GLS. The results show that the estimation of MASEM using GMM yields the SE value in each coefficient is smaller than the estimation of MASEM using GLS. Interactive GMM for the determination of the optimal weight on GMM in this study gave better results and therefore needs to be developed in order to obtain a Random Model MASEM estimator using GMM that is much more reliable and accurate in performance.
Highlights
The estimation results of Meta-Analytical Structural Equation Modeling (MASEM) using the Generalized Method of Moments (GMM) are tested on simulation data to show the performance of the GMM method and the results are compared to the
The estimation of Meta-Analytical Structural Equation Modeling (MASEM) with the GMM method was applied to the case real data in the article [15] with size of sample
The Meta-Analytic Structural Equation Modeling (MASEM) estimator with GMM was proven to be unbiased and consistent; it has the goodness of the estimator
Summary
There are many scientific studies whose discussions have the same topic but with various characteristics and results. Those studies are conducted from time to time and space to space on several global problems with the same goals. This condition demands researchers to review those scientific studies known as literature review. Statistical methods that are capable of synthesizing studies, integrating studies, and gathering evidence of the studies, for the purpose of integrating findings of those studies, are called a meta-analysis [2]. One of the requirements needed in a meta-analysis is an assessment of the results of similar studies by finding the effect size value
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