scholarly journals Structural equation modeling and principal component analysis of gray matter volumes in major depressive and bipolar disorders: Differences in latent volumetric structure

2010 ◽  
Vol 184 (3) ◽  
pp. 177-185 ◽  
Author(s):  
Ping-Hong Yeh ◽  
Hongtu Zhu ◽  
Mark A. Nicoletti ◽  
John P. Hatch ◽  
Paolo Brambilla ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Structural Equation Modeling ◽  
Gray Matter ◽  
Structural Equation ◽  
Bipolar Disorders ◽  
Principal Component ◽  
Component Analysis ◽  
Equation Modeling ◽  
Major Depressive ◽  
Gray Matter Volumes

scholarly journals Cutoff criteria for overall model fit indexes in generalized structured component analysis

2020 ◽  
Vol 8 (4) ◽  
pp. 189-202
Author(s):  
Gyeongcheol Cho ◽  
Heungsun Hwang ◽  
Marko Sarstedt ◽  
Christian M. Ringle
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Component Analysis ◽  
Model Fit ◽  
Equation Modeling ◽  
Generalized Structured Component Analysis ◽  
Root Mean Square Residual ◽  
Fit Indexes ◽  
Cutoff Criteria

AbstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

scholarly journals Structural Equation Modeling of the Factors Affecting the Nutritional Status of Children Under Five in Banyuwangi Region using Recursive (one-way) GSCA

2015 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
I Made Tirta ◽  
Nawal Ika Susanti ◽  
Yuliani Setia Dewi
Keyword(s):  
Structural Equation Modeling ◽  
Nutritional Status ◽  
Structural Equation ◽  
Economic Status ◽  
Bootstrap Method ◽  
Component Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Parameter Estimates

Structural Equation Modeling is one among popular multivariate analysis, especially applied in pschology and marketing. There are two main types of Structural Equation Modeling namely covariance-based or CB-SEM and variance-based or Partial Least Square (PLS)- SEM. Both types have advantages and disadvantage. To overcome its limitation, Generalized Structured Component Analysis (GSCA) was then proposed as an extension of PLS-SEM. In estimating the parameters, GSCA uses Alternating Least Squares (ALS) and in estimating the standard error of the parameter estimates it uses the bootstrap method. In this paper, GSCA is applied to study the causality model of Infant nutritional status, in relation with socio-economic status and infantcare status in Banyuwangi Region. The results show that both socio-economic and infantcare status have significant positive influence on infant nutritional status.Keywords:  Alternating least square, generalized structural component analysis,  nutritional status of infants,  structural equation modelling

scholarly journals ANALISIS DERAJAT KESEHATAN MASYARAKAT PROVINSI BALI DENGAN MENGGUNAKAN METODE GENERALIZED STRUCTURED COMPONENT ANALYSIS (GSCA)

2013 ◽  
Vol 2 (2) ◽  
pp. 54
Author(s):  
PUTU NOPITA PURNAMA NINGSIH ◽  
KETUT JAYANEGARA ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Structural Equation Modeling ◽  
Health Status ◽  
Health Service ◽  
Structural Equation ◽  
Component Analysis ◽  
Equation Modeling ◽  
Multivariate Normal ◽  
Behavioral Economic ◽  
Generalized Structured Component Analysis ◽  
The Relationship

The aim of this research is to determine the relationship between environmental, behavioral, health services, education, and economic variables to health status in the Province of Bali. These variables are constructs (latents ) that can not be measured directly by observation. If there was a relationship between latent and its indicators, it is recomended to use Structural Equation Modeling (SEM). In this research we used variance-based SEM i.e. Generalized Structured Component Analysis (GSCA). This method not based on many assumptions such as the data does not have a multivariate normal distribution, the sample size does is not necessary large. Moreover, GSCA provides by overall goodness-fit of the model. The result of this research indicates that the environmental, behavioral, economic and educational variable influenced health status, but health service does not significantly affect the health status; economic does not significantly affect the environment; and education does not significantly affect the behavior. The result of the FIT value ?0.450 and the AFIT value 0.429 showed that overall model in this research is not good enough because of both of these values are under 0.50.

scholarly journals Engineering Consultancy Practice (ECP) Business Model in Malaysia: A Structural Equation Modeling (SEM) Approach

2016 ◽  
Vol 11 (3) ◽  
pp. 52
Author(s):  
Justin Lai ◽  
Rosli Zin Khairulzan Yahya ◽  
Chai Chang Saar
Keyword(s):  
Structural Equation Modeling ◽  
Business Model ◽  
Structural Equation ◽  
Business Performance ◽  
Principal Component ◽  
Equation Modeling ◽  
Management Capability ◽  
Local Stakeholders ◽  
Successful Business ◽  
Analyze Data

<p>The implementation of liberalization in Malaysia has offered opportunities to the Malaysian to expand business. The salient point of liberalization of Engineering Consultancy Practices (ECP) is the opening of the flood gate for non-professionals (including foreigners) to register and operates consultancy practices. This would create an excessive competitive environment to the Malaysian ECP. The aim of this study is to identify the successful business model to be adopted by Engineering Consultancy Practice (ECP) for building its capacity and competitiveness. This study is important in the sense that it serves as one of the pioneer studies, focusing on the engineering consultancy practices, from the perspective of business model. Principal Component Analysis (PCA) is employed to analyze data from a quantitative survey. Three components are extracted through PCA approach: (1) Profit Structure factor, (2) Management Capability factor and (3) Stakeholder Relationship factor. Consequently, Structural Equation Modeling (SEM) is utilized to perform analysis on the data extracted from PCA. Two (2) Business Model Indices are formed to examine the business performance in terms of business model criteria and business performance. Through the data validation, it is found that ECP Business Performance Index is best to evaluate the business performance. Understanding the core values related to the Engineering Consultancy Practices could help the local stakeholders to have better preparation and planning to face a greater challenge lies as a result of the liberalization.</p>

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