Structural Equation Modelling

& Path Analysis Resources

Performed by

SmartPLS

Prof. Livre Docente Otávio J. OliveiraBolsista Produtividade DT/CNPqe-mail: otavio@feb.unesp.br 

Currículo: http://lattes.cnpq.br/8045074316518664FEG/UNESP

Contact student:

Francesco AndreoliETH Zuerich, Switzerlande-mail: francesco.andreoli@hotmail.com

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: raphaella@globo.com

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

1 part

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

SmartPlS Quick Tutorial

Source: http://www.smartpls.de/

Create new project

Model creation

Import data

If the variable become color blu the data input and the model is correct

And then simulate:

Report

Model design

Data input

simulation Variable insertion

Box description

Resume

Our Final case examinated in SmartPLS

Questionnaire development

Answer range from 1 to 5

Excel data

Case studied

Question nr. Supp. Infos

Quest. res

Data input in smartPLS

This Matrix is only a preview!! The all data is in

Construct

Benefit

Difficulties

Performance

Model in SmartPLS

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

2 part

Tutorial video