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SmartPLS presentation
- 1. Structural Equation Modelling & Path Analysis Resources Performed by SmartPLS Prof. Livre Docente Otávio J. Oliveira Bolsista Produtividade DT/CNPq e-mail: otavio@feb.unesp.br Currículo: http://lattes.cnpq.br/8045074316518664 FEG/UNESP
- 2. Contact student: Raphaella deM. Cezar Trainee - Jr. Eng.Eng. de Produção Mecânica UNESP Guaratinguetá Cel.: (12) 8172 6064 e-mail: raphaella@globo.com Francesco Andreoli ETH Zuerich, Switzerland e-mail: francesco.andreoli@hotmail.com http://www.linkedin.com/in/francescoandreoli
- 3. Goal Showingthe 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
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- 5. Overview of thepresentation • Intro •Path diagram •Software •Worked Example •Data collection •Model design •Hypotesis •Simulation and parameter estimates •Overview of the results
- 6. Refresh • Correlation – linear relationship between two variables – range from -1 to +1 • Covariance – unstandardised form of correlation – positive number positive relationship
- 7. • 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
- 8. Software on market •Lavaan •Sem package in R programmation •EQS •Mplus •SPSS Amos •SmartPLS •Partial Least Squares •theory and measures simultaneously examination
- 9. Graphical Vocabulary Observed Variable Latent variable Error Predictive relationship (Cov) correlation
- 10. SmartPlS Quick Tutorial Source: http://www.smartpls.de/
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- 26. If the variablebecome color blu the data input and the model is correct
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- 29. Resume simulation Variable insertion Model design Data input Box description
- 30. Our Final caseexaminated in SmartPLS
- 31. Questionnaire development Answerrange from 1 to 5
- 32. Excel data Question nr. Supp. Infos Case studied Quest. res
- 33. Data input insmartPLS This Matrix is only a preview!! The all data is in
- 35. Construct Model in SmartPLS Benefit Difficulties Performance
- 36. 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
- 37. Trust field •Reliability: Thisis 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.
- 38. Result Quality criteria overview 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 0,0182 cont 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
- 39. 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 0 cont 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 0 cont 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
- 40. Sources: http://web.psych.unimelb.edu.au/jkanglim/Introduction toSEM.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
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