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SmartPLS is a software application for (graphical) path modeling with latent variables (LVP). The partial least squares (PLS)-method is used for the LVP-analysis in this software.
Citation preview
Structural Equation Modelling
& Path Analysis Resources
Performed by
SmartPLS
Prof. Livre Docente Otávio J. OliveiraBolsista Produtividade DT/CNPqe-mail: [email protected]
Currículo: http://lattes.cnpq.br/8045074316518664FEG/UNESP
Contact student:
Francesco AndreoliETH Zuerich, Switzerlande-mail: [email protected]
http://www.linkedin.com/in/francescoandreoli
Raphaella de M. Cezar
Trainee - Jr. Eng.Eng. de Produção Mecânica
UNESP Guaratinguetá
Cel.: (12) 8172 6064
e-mail: [email protected]
Goal
Showing the student the main properties of SmartPLS software used for basic statistical treatments.
1 part
Overview of the situation and presentation of the software.
2 part
Video showing how SmartPLS works
Overview of the presentation
• Intro
•Path diagram
•Software
•Worked Example
•Data collection
•Model design
•Hypotesis
•Simulation and parameter estimates
•Overview of the results
Refresh
• Correlation– linear relationship between two variables
– range from -1 to +1
• Covariance– unstandardised form of correlation
– positive number positive relationship
• Latent variable
– not measured directly in a study
– assumed to bring about the observed responses
• Observed variables
– directly measured in a study
• Exogenous variables
– assumed to be external to the model
– only have double headed arrows (i.e., correlation)
• endogenous variables
– predicted by other variables in the model
– directed arrow entering into them
Software on market
•Lavaan
•Sem package in R programmation
•EQS
•Mplus
•SPSS Amos
•SmartPLS
•Partial Least Squares
•theory and measures simultaneously examination
Graphical Vocabulary
Observed Variable
Latent variable
Error
Predictive relationship (Cov)
correlation
Coeff definition review
•AVE
• average value
•Reability
•equal factor loadings misured
• variance portion rapresentation
•Composite reability
•overall reliability of a collection of heterogeneous
•R square
•coefficient of determination, measuring the amount of variation accounted for in the endogenous constructs by the exogenous constructs
•Cronbach’s α
•lower-bound estimate for the composite score reliability
•Reliability: This is demonstrated by Composite Reliability greater than 0.700.
•Convergent Validity: This is demonstrated by loadings greater than 0.700, AVE greater than 0.500, and Communalities greater than 0.500
•Discriminant validity: This is demonstrated by the square root of the AVE being greater than any of the inter-construct correlations.
Trust field
Result
AVE Composite Reliability R Square Cronbachs Alpha Communality Redundancy HR 0,6629 0,854 0,3498 0,742 0,6629 0,2307 benefit 0,6167 0,8642 0,56 0,7941 0,6167 0,0182cont improvement 0,7364 0,8932 0,6124 0,8198 0,7364 0,246 costumers 0,735 0,8925 0 0,8202 0,735 0 difficulties 0,3922 0,1331 0,2363 0,2717 0,3922 0,0419 performance 0,4084 0,807 0,4731 0,728 0,4084 0,0275 standardization 0,7621 0,9057 0,4953 0,8437 0,7621 -0,1583 suppliers 0,8242 0,9336 0,3851 0,893 0,8242 0,0657
Quality criteria overview
Path coefficient
HR benefit cont improvement costumers difficulties performance standardization suppliers HR 0 0,0342 0,3447 0 -0,2366 0,0804 -0,2318 0,2123 benefit 0 0 0 0 -0,0355 0 0 0cont improvement 0 -0,0033 0 0 0,0137 -0,0167 0,6638 -0,0516 costumers 0,5915 0,5414 0,5277 0 -0,0302 0,5837 0,2213 -0,1639 difficulties 0 0 0 0 0 -0,0719 0 0 performance 0 0 0 0 0 0 0 0 standardization 0 0,2212 0 0 -0,2935 -0,144 0 0,6544 suppliers 0 0,0831 0 0 -0,0292 0,2635 0 0
Path coefficient total Effect HR benefit cont improvement costumers difficulties performance standardization suppliers HR 0 0,0484 0,3447 0 -0,2383 0,1429 -0,0031 0,1925 benefit 0 0 0 0 -0,0355 0,0026 0 0cont improvement 0 0,1753 0 0 -0,1985 0,0029 0,6638 0,3828 costumers 0,5915 0,7099 0,7316 0 -0,3612 0,6411 0,5697 0,2967 difficulties 0 0 0 0 0 -0,0719 0 0 performance 0 0 0 0 0 0 0 0 standardization 0 0,2755 0 0 -0,3224 0,0516 0 0,6544 suppliers 0 0,0831 0 0 -0,0321 0,2658 0 0
Sources:
http://web.psych.unimelb.edu.au/jkanglim/IntroductiontoSEM.pdf
http://www.smartpls.de/forum/index.php
http://statwiki.kolobkreations.com/wiki/PLS
PLS Reliability and validity
http://statwiki.kolobkreations.com/wiki/PLS
http://zencaroline.blogspot.com.br/2007/06/composite-reliability.html