smart_pls_guide.github.io/guide.Rmd at master · ariff118/smart_pls_guide.github.io · GitHub

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---
title: "Analysis Guidelines"
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## 1.	Preparation

  i) Missing values in SPSS need to be addressed.
  ii) Save SPSS file as csv format.
  iii) Remove variables/data which are not needed, such as respondent profile in csv file.

## 2.	Getting Started with PLS

  i) Create new project
  ii) Double-click to import data.
  iii) Draw diagram on workplace.

## 3.	Path Modeling (Reflective indicators)

  i) Assessment of measurement model (PLS algorithm)
      a.	Convergent validity (Outer loadings, AVE and CR)
      b.	Discriminant validity (Fornell & Larcker and HTMT)
  ii) Assessment of structural model
      a.	Assessment of collinearity (VIF) (PLS algorithm)
      b.	Assessment of path coefficient (Bootstrapping)
      c.	Coefficient of Determination (R square) (PLS algorithm)
      d.	Effect size (f square) (PLS algorithm)
      e.	Predictive relevance (Q square) (Blindfolding)

## 4.	Mediation Analysis
  i) Assessment of measurement model (PLS algorithm)
      a.	Convergent validity (Outer loadings, AVE and CR)
      b.	Discriminant validity (Fornell & Larcker and HTMT)
  ii)	Assessment of structural model
      a.	Assessment of collinearity (VIF) (PLS algorithm)
      b.	Assessment of path coefficient (Bootstrapping)
      c.	Assessment of indirect effect: (Bootstrapping 2-tailed)
      d.	Coefficient of Determination (R square) (PLS algorithm)
      e.	Effect size (f square) (PLS algorithm)
      f.	Predictive relevance (Q square) (Blindfolding)

## 5.	Moderator Analysis (categorical data, which requires dummy coding)

  i) Draw diagram, include moderator as IV
  ii) Assessment of measurement model (PLS algorithm)
        a.	Convergent validity (Outer loadings, AVE and CR)
        b.	Discriminant validity (Fornell & Larcker and HTMT)
        c.	Assessment of R square and f square before moderation
  iii) Add moderating effect, identify moderator and IV, select product indicator and unstandardized product term
  iv) Assessment of structural model
        a.	Assessment of collinearity (VIF) (PLS algorithm)
        b.	Assessment of path coefficient (Bootstrapping)
        c.	Assessment of path coefficient of moderation (Bootstrapping)
        d.	Coefficient of Determination (R square) (PLS algorithm)
        e.	Effect size (f square) (PLS algorithm)

## 6.	Moderator Analysis (continuous data)

  i) Draw diagram, include moderator as IV
  ii) Assessment of measurement model (PLS algorithm)
        a.	Convergent validity (Outer loadings, AVE and CR)
        b.	Discriminant validity (Fornell & Larcker and HTMT)
        c.	Assessment of R square and f square before moderation
  iii) Add moderating effect, identify moderator and IV, select product indicator and mean centered product term
  iv) Assessment of structural model
        a.	Assessment of collinearity (VIF) (PLS algorithm)
        b.	Assessment of path coefficient (Bootstrapping)
        c.	Assessment of path coefficient of moderation (Bootstrapping)
        d.	Coefficient of Determination (R square) (PLS algorithm)
        e.	Effect size (f square) (PLS algorithm)

## 7.	Analysis with HOC Independent Variables (Type II) – Two Stage Approach

  i) Draw links between the first order constructs and the endogenous variables.
  ii) Run PLS Algorithm and assess the measurement model
  iii) Assessment of measurement model (PLS algorithm)
        a.	Convergent validity of first order constructs and endogenous variables (Outer loadings, AVEand CR)
        b.	Discriminant validity among first order constructs and endogenous variables (Fornell & Larcker and HTMT)
  iv) Once measurement model is satisfactory, obtain “Latent Variable Score” from algorithm output.
  v) Copy and paste the “Latent Variable Score” into new excel sheet and save as .csv file
  vi) Import the Latent Variable Score csv file into SmartPLS, then develop a new path model using the new dataset
  vii) Load the first order construct (now indicator) as indicator for second order construct and
        a.	Assessment of weight significance of the indicators (first order) on second order construct (Bootstrapping)
        b.	Assess collinearity for first order formative indicators (VIF)
        c.	Conduct redundancy analysis between the new construct with formative indicators and a single global item constructs
  viii)	Link the new construct with the original endogenous variables
  ix) Assessment of structural model
      a.	Assessment of collinearity (VIF) (PLS algorithm)
      b.	Assessment of path coefficient (Bootstrapping)
      c.	Coefficient of Determination (R square) (PLS algorithm)
      d.	Effect size (f square) (PLS algorithm)
      e.	Predictive relevance (Q square) (Blindfolding)