2-Day Workshop

2-Day Workshop on PLS Path Modeling (June 15th-16th, 2017)

After a return to the origins of structural equation modeling (SEM), the PLSPM algorithm will be presented. A methodology to interpret results will then be suggested on the basis of real life cases. The training session will be illustrated by applications using XLSTAT.

DAY 1: Algorithm, Estimation and Practice

  • Introduction to Structural Equation Modeling
    • Covariance-based and Component-based apporaches

  • PLS Path Modeling Algorithm
    • PLS Path Modeling algorithm for model estimation:
      • Measurement (Outer) Model Specification and Estimation Modes (Reflective vs. Formative - Mode A and Mode B)
      • Structural (Inner) Model Specification and Estimation Schemes (Centroid - Factorial - Path Weighting Schemes)
      • PLS algorithm for computing Latent Variable Scores
    • PLS Algorithm for the case of one and two blocks:
      • Principal Component Analysis, Tucker°Øs Inter-battery Analysis, Canonical Correlation Analysis, PLS Regression, Redundancy Analysis
    • Hierarchical PLS-PM and the super-block option

  • Introductory Tutorial on XLSTAT-PLSPM with Case Studies
    • Model Specification: exploring graphical interface features
    • Model Estimation: measurement and structural options
    • Scaling Latent Variable Scores: standardized vs. normalized
    • Output Retrieval (graphical and tabular) and Interpretation:
      • Outer weights, normalized weights, standardized loadings
      • Path coefficients (direct, indirect and total effects), R2, standardized path coefficients, contribution to R2, simple and partial correlations
    • Latent variables scores (casewise values, summary statistics)

DAY 2: Model Assessment, Improvement and Advances in PLS-PM

  • Model Assessment and Improvement: Diagnostics and Solutions
    • Convergent validity: composite reliability, eigenvalues, condition number, critical value, weights and loadings, average variance extracted (AVE), communality
    • Discriminant validity: cross-loadings vs. loadings, latent variables correlations vs. AVE
    • Predictive relevance: Redundancy, R2, Absolute and Relative Goodness of Fit (GoF), Effect Size f2
    • Statistical significance:? Bootstrapping, Jackknifing, t-test, F-test, critical ratios
    • Cross-validation: Blindfolding, CV-Communality, CV-Redundancy
    • Handling Missing Data:? Lohm?ller°Øs option, Impact on Latent Variable Scores
  • Continuous Moderating Effects
    • Why & How to Investigate Moderating Effects?
    • Discrete (categorical) vs. continuous moderator variable
    • Methods for Assessing Interaction Effects: Product-Indicator, Two-Stage, Hybrid, Orthogonalizing
    • Interaction with Formative Indicators
    • Centering or Standardizing the Indicators
    • Choosing the appropriate method
    • Additional Methods for Non Linear Relations: Measurement and Structural Level
  • Discrete Moderating Effects: Multi-Group Comparison
    • Bootstrap parametric approaches: t-test, empirical confidence intervals
    • Permutation-based comparisons
  • Mediating Effects
    • Mediator vs. Confounder
    • Causal Steps for Testing Mediation
    • Methods for Assessing Mediating Effects: Sobel, resampling
    • Mediator versus Moderator
    • Moderated Mediation
  • Handling Multidimensionality
    • Detection of Block Multidimensionality
    • Mode PLS for the Measurement Model: a continuum from Mode A to Mode B
    • PLS Regression to cope with multicollinearity in the Structural Model
  • Uncovering Segments
    • Definition of Unobserved Heterogeneity
    • REBUS-PLSPM
  • This is the only Workshop that provides training on the most comprehensive PLS software package - XLSTAT-PLSPM (http://www.xlstat.com/en/products/xlstat-plspm/). The detailed agenda and registration procedure are available at:https://www.xlstat.com/en/training/a-2-day-workshop-on-pls-path-modeling-via-xlstat-software-china