HW2: Search an article with a structural model and covariance matrix among indicators (caution: do not use the correlations between latent variables). Reflective: convergent, discriminant validity and reliability Path analysis from covariance matrix and from raw data (dataset)Ĭonfirmatory factor analysis and restrictions on parameters
Software R, R packages, install packages, load packages Sample size and statistical power with G*Power 3
Estimate the full model, adjust the measurement model and report and explain the results. HW1: (i) multicollinearity + 2nd order LV (ii) importance-performance map analysis Multigroup analysis: observed heterogeneity (a priori) sample size and statistical power with G*Power 3 Multicollinearity in the structural model Formative variable in exogenous and endogenous positionįull model – path analysis with latent variables in SmartPLS convergent and discriminant validity, and reliabilityĮmergent variables or Formative latent variables Software SPSS or Minitab or R (Rcmdr package) Reflective latent variable and principal components. Path analysis with observed variables: indirect, direct and total effects Linear regression: betas, R² e bootstrap How to use SmartPLS: data, project, files New York: Routledge, 2014.Įxploratory and confirmatory analysis (Theory and Data) Latent Variable Modeling Using R: a step-by-step guide. Asheboro, NC: Statistical Associates Publishers. Partial Least Squares: Regression and Structural Equation Models. Thousand Oaks, CA: Sage Publications, Inc., 2017. Advanced Issues in Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: Sage Publications, Inc., 2016. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Suggestion for students, who want to buy books, to facilitate the study: The instructions will be send before the course beginning)