ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R

Holipah Holipah, I. Tirta, Dian Anggraeni
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引用次数: 4

Abstract

Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. Keywords: SEM, Multiple Group, R Program
分析结构方程模型(sem)邓安多群蒙古纳坎等
结构方程模型(SEM)是一种同时处理测量误差、指标变量和潜在变量的统计技术。扫描电镜是用来测试假设,说明潜变量之间的关系时,潜变量已通过每个指标变量进行评估。多组SEM是使用多个样本的基本模型分析。该分析旨在确定两个样本组的测量和结构模型的成分或模型是否不变。在本研究中,对数据产生了一些需求。首先,生成样本量n = 250的数据。第一个生成的数据为同质数据,测量模型与第1组和第2组的结构模型相同;第二个生成的数据为非同质数据,测量模型与第1组和第2组的结构模型不相同。利用R中提供的lavaan软件包对数据进行分析,从形成的部分数据中得到SEM估计结果和拟合优度模型。从两组合并的结果可以看出,df(63)最大的两个模型的不变量Fit Mean模型是最简单的模型。然而,最小的df(48)与Fit。配置模型是最复杂的模型。关键词:SEM,多组,R程序
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