Comparative approach on structural equation modeling software applications

2018 ◽  
Author(s):  
Rosmery Ramos Sandoval ◽  
Jano Ramos-Diaz
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Comparative Approach ◽  
Software Applications ◽  
Modeling Software

Application of Structural Equation Modeling Software in Applied Linguistics

2014 ◽  
Vol 687-691 ◽  
pp. 1573-1576
Author(s):  
Wei Jing
Keyword(s):  
Structural Equation Modeling ◽  
Literature Review ◽  
Uniform Distribution ◽  
Structural Equation ◽  
Applied Linguistics ◽  
Literature Survey ◽  
Equation Modeling ◽  
General Situation ◽  
Modeling Software

Mechanical drawing language EQS, its full name is Equally Spaced, which means the uniform distribution of meaning. Now, its importance is more and more incarcerating. This paper outlined the application of EQS in Applied Linguistics, firstly introduces the general situation, then describes the modeling steps; finally applied linguistics tells the story of EQS. In this paper, it mainly used the literature review method and literature survey.

Using WarpPLS in E-collaboration Studies

2010 ◽  
Vol 6 (4) ◽  
pp. 1-11 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Research Methods ◽  
Latent Variables ◽  
Structural Equation ◽  
Software Tools ◽  
Equation Modeling ◽  
Modeling Analysis ◽  
Modeling Software ◽  
S Curve ◽  
Complex Phenomena

Most relationships between variables describing natural and behavioral phenomena are nonlinear, with U-curve and S-curve relationships being particularly common. Yet, structural equation modeling software tools do not estimate coefficients of association taking nonlinear relationships between latent variables into consideration. This can lead to misleading results, particularly in multivariate and complex phenomena like those related to e-collaboration. One notable exception is WarpPLS (available from: warppls.com), a new structural equation modeling software currently available in its first release. The discussion presented in this paper contributes to the literature on e-collaboration research methods by providing a description of the main features of WarpPLS in the context of an e-collaboration study. The focus of this discussion is on the software’s features and their use and not on e-collaboration study itself. Particular emphasis is placed on the five steps through which a structural equation modeling analysis is conducted through WarpPLS.

Using WarpPLS in E-Collaboration Studies

2012 ◽  
pp. 62-78
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Virtual Teams ◽  
Structural Equation ◽  
Research Literature ◽  
Previous Article ◽  
Equation Modeling ◽  
Modeling Analysis ◽  
Modeling Software ◽  
Nonlinear Structural Equation

This is a follow-up on a previous article (Kock, 2010b) discussing the five main steps through which a nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (warppls.com). Both this and the previous article use data from the same E-collaboration study as a basis for the discussion of important WarpPLS features. The focus of this article is on specific features related to saving and analyzing grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving the various minor and major results of the analysis. Even though its focus is on an E-collaboration study, this article contributes to the broad literature on multivariate analysis methods, in addition to the more specific research literature on E-collaboration. The vast majority of relationships between variables, in investigations of both natural and behavioral phenomena, are nonlinear; usually taking the form of U and S curves. Structural equation modeling software tools, whether variancE- or covariancE-based, typically do not estimate coefficients of association based on nonlinear analysis algorithms. WarpPLS is an exception in this respect. Without taking nonlinearity into consideration, the results can be misleading; especially in complex and multi-factorial situations such as those stemming from E-collaboration in virtual teams.

scholarly journals Habilidades directivas y clima organizacional en pequeñas y medianas empresas

2021 ◽  
Vol 50-1 ◽  
pp. 1-23
Author(s):  
Daniel Paredes-Zempual ◽  
Luis Enrique Ibarra-Morales ◽  
Zahira Esther Moreno-Freites
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Modeling Software

Actualmente, los gerentes deben aprender a utilizar y administrar las diferentes habilidades directivas en función de un buen clima organizacional. Objetivo: Determinar el grado de asociación entre habilidades directivas y clima organizacional de las PyMes de Villa Juárez, Sonora. Método: Fue una investigación descriptiva y cuantitativa. Se aplicó un cuestionario a directivos de 53 PyMes. Resultados: Se utilizó la técnica de mínimos cuadrados parciales (PLS), mediante la construcción de un modelo SEM (Structural Equation Modeling) software Smart PLS [v.3.3.0]. Se demostró que las variables latentes: negociación (ξ1) y liderazgo (ξ3) son significativas para el clima organizacional (η1; R2=0.804). Originalidad: Determinar las variables exógenas que explican la varianza de la variable endógena de las PyMes. Hallazgos: El efecto del f2 en la relación entre η1 y ξ1 es alto (f2=0.710); mientras que, para η1 y ξ3, el efecto es bajo (f2=0.104). Limitaciones: Reducido número de empresas en el municipio.

Using WarpPLS in E-Collaboration Studies

2011 ◽  
pp. 180-190 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Research Methods ◽  
Latent Variables ◽  
Structural Equation ◽  
Software Tools ◽  
Equation Modeling ◽  
Modeling Analysis ◽  
Modeling Software ◽  
S Curve ◽  
Complex Phenomena

Most relationships between variables describing natural and behavioral phenomena are nonlinear, with U-curve and S-curve relationships being particularly common. Yet, structural equation modeling software tools do not estimate coefficients of association taking nonlinear relationships between latent variables into consideration. This can lead to misleading results, particularly in multivariate and complex phenomena like those related to e-collaboration. One notable exception is WarpPLS (available from: warppls.com), a new structural equation modeling software currently available in its first release. The discussion presented in this paper contributes to the literature on e-collaboration research methods by providing a description of the main features of WarpPLS in the context of an e-collaboration study. The focus of this discussion is on the software’s features and their use and not on e-collaboration study itself. Particular emphasis is placed on the five steps through which a structural equation modeling analysis is conducted through WarpPLS.

Analisis Tingkat Penerimaan Mahasiswa Terhadap Cloud File Hosting Services dengan Metode Technology Acceptance Model

2016 ◽  
Vol 6 (2) ◽  
pp. 136-139
Author(s):  
Andrianus Bennyanto ◽  
Marcelli Indriana
Keyword(s):  
Structural Equation Modeling ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Equation Modeling ◽  
Equation Modelling ◽  
Modeling Software ◽  
Index Terms ◽  
Google Drive ◽  
Acceptance Model

There are many mobile and desktop apps available to use for free. Starting from games to productivity apps. One type of productivity apps is cloud file hosting services such as Dropbox and Google Drive. This study aims to determine how Dropbox and Google Drive are accepted to the users. Not just want to get the factors of acceptance, but to get the root of the acceptance. By using the methodology of technology acceptance model and relying on statistical calculations of structural equation modeling software LISREL, the level of acceptance of these two popular applications will be known. Index Terms - Cloud Fire Hosting Services, Level of Acceptance, Technology Acceptance Model, Structural Equation Modelling, LISREL.

Using WarpPLS in e-Collaboration Studies

2011 ◽  
Vol 7 (2) ◽  
pp. 1-18 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Virtual Teams ◽  
Structural Equation ◽  
Research Literature ◽  
Previous Article ◽  
Equation Modeling ◽  
Modeling Analysis ◽  
Modeling Software ◽  
Nonlinear Structural Equation

This is a follow-up on a previous article (Kock, 2010b) discussing the five main steps through which a nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (warppls.com). Both this and the previous article use data from the same e-collaboration study as a basis for the discussion of important WarpPLS features. The focus of this article is on specific features related to saving and analyzing grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving the various minor and major results of the analysis. Even though its focus is on an e-collaboration study, this article contributes to the broad literature on multivariate analysis methods, in addition to the more specific research literature on e-collaboration. The vast majority of relationships between variables, in investigations of both natural and behavioral phenomena, are nonlinear; usually taking the form of U and S curves. Structural equation modeling software tools, whether variance- or covariance-based, typically do not estimate coefficients of association based on nonlinear analysis algorithms. WarpPLS is an exception in this respect. Without taking nonlinearity into consideration, the results can be misleading; especially in complex and multi-factorial situations such as those stemming from e-collaboration in virtual teams.

Sign in / Sign up

Export Citation Format

Share Document