Introduction to R and to SEM using the lavaan package
  • Introduction to Course and to R (slides)
  • Introduction to Path Modeling and SEM (slides, part 1)
  • Introduction to Path Modeling and SEM (slides, part 2)
  • Input and Output into R
  • Useful Data Summary Statistics
  • JSS Reading and Exercise #1
  • What is lavaan (up to syntax) ?
  • Estimate an Example Confirmatory Factor Analysis (CFA)
  • Other Useful lavaan Fitted Results Functions
Confirmatory Factor Analysis (CFA) with lavaan
  • Exercise Solutions from Section 1
  • SEM Review (slides, part 1)
  • SEM Review (slides, part 2)
  • SEM Review (slides, part 3)
  • Run CFA in R Script (part 1)
  • Run CFA in R Script (part 2)
  • Run CFA in R Script (part 3)
  • Run CFA in R Script (part 4)
  • CFA Exercise
Full SEM Models
  • Solution to CFA Exercise from Section 2 (part 1)
  • Solution to CFA Exercise from Section 2 (part 2)
  • Full SEM Political Democracy Model Example (part 1)
  • Full SEM Political Democracy Model Example (part 2)
  • Full SEM Political Democracy Model Example (part 3)
  • Full SEM Quantitative Attitudes Example (part 1)
  • Full SEM Quantitative Attitudes Example (part 2)
  • Setting Inequalities Full SEM Exercise
Factor Analysis
  • What is Factor Analysis ?
  • Set Up Data for Factor Analysis
  • Begin Performing Exploratory Factor Analysis (EFA)
  • Continue Performing Various EFAs
  • Perform a Confirmatory Factor Analysis (CFA)
Missing Data and Imputation
  • Introduction to Missing Data and Imputation
  • Solution to Setting Inequalities Exercise from Section 3 (part 1)
  • Solution to Setting Inequalities Exercise from Section 3 (part 2)
  • Solution to Setting Inequalities Exercise from Section 3 (part 3)
  • Missing Data Problems and Issues (part 1)
  • Missing Data Problems and Issues (part 2)
  • Missing Data Imputation R Scripts Examples (part 1)
  • Missing Data Imputation R Scripts Examples (part 2)
  • More R Scripts with Modification Indices and FIML
  • Missing Data Exercise and an Audience Question
Mediation and Indirect Effects
  • Introduction to Mediation and Indirect Effects
  • Solution to Missing Data Exercise from Section 5 (part 1)
  • Solution to Missing Data Exercise from Section 5 (part 2)
  • Mediation Concepts (slides, part 1)
  • Mediation Concepts (slides, part 2)
  • First R Script Mediation Example
  • Second R Script Mediation Example (part 1)
  • Second R Script Mediation Example (part 2)
  • Mediation Exercise
  • More on the Complexity of Mediation
Estimating Group Effects
  • Introduction to Estimating Group Effects and Moderation
  • Solution to Mediation Exercise from Section 6
  • Introduction to Meanstructures; Group Effects Slides
  • Group Analysis Functions in lavaan
  • Groups R Script CFA Example
  • Constraining Parameters Across Groups
  • Multi-Group Analysis Measurement Invariance Example (part 1)
  • Multi-Group Analysis Measurement Invariance Example (part 2)
Latent (Growth) Curve Models
  • Introduction to Latent (Growth) Curve Models
  • First LCM Example (part 1)
  • Add Covariates to First LCM Example
  • Crime Data LCM Example (part 1)
  • Crime Data LCM Example (part 2)
  • Crime Data LCM Example (part 3)
  • Crime Data LCM Example (part 4)
  • Latent Curve Models Review
  • Review LCM Crime Models 1 and 2
  • Review LCM Crime Models 3, 4 and 5
  • Adding Covariates and MIMIC
  • More on Covariates and Interactions
  • Alternative Specifications of Latent Intercepts and Slopes
  • Alternative Specification of Multigroup Models (exercise solution)