Table of Contents Data Input Stacked Models in Lavaan Model Comparison Using lavaan
Made for Jonathan Butner’s Structural Equation Modeling Class, Fall 2017, University of Utah. This handout will focus on implementing stacked models in lavaan, which allow us to test a model for two different groups (for example, control vs. intervention). This syntax imports the X variable, 192 person dataset called HW9 2017.

Table of Contents Data Input Structural Equation Modeling Using lavaan: Measurement Model Structural Equation Modeling Using lavaan: Full Model Model Comparison Using lavaan Interpreting and Writing Up Your Model
Made for Jonathan Butner’s Structural Equation Modeling Class, Fall 2017, University of Utah. This handout begins by showing how to import a matrix into R. Then, we will overview how to establish a measurement model in R using the lavaan package.

Table of Contents Data Input Confirmatory Factor Analysis Using lavaan: Factor variance identification Model Comparison Using lavaan Calculating Cronbach’s Alpha Using psych
Made for Jonathan Butner’s Structural Equation Modeling Class, Fall 2017, University of Utah. This handout begins by showing how to import a matrix into R. Then, we will overview how to complete a confirmatory factor analysis in R using the lavaan package.

Table of Contents Data Input Scree Plot and Parallel Analysis Minimum Average Partial Factor Extraction Orthogonal Rotation Using Varimax Oblique Rotation Using Direct Oblimin
Made for Jonathan Butner’s Structural Equation Modeling Class, Fall 2017, University of Utah. This handout begins by showing how to import a matrix into R. Then, we will overview how to determine number of factors, or dimensions, to extract from your data.

Table of Contents Data Input Introduction to Lavaan Inspecting matrices when things go wrong Modeling in Lavaan Using a Covariance Matrix
Made for Jonathan Butner’s Structural Equation Modeling Class, Fall 2017, University of Utah. This handout will serve as an introduction to the lavaan package in R, which can be used for structural equation modeling. Mainly, we will focus on how path models can be conducted simply as a series of regressions in the R package lavaan, including estimation of indirect effects with bootstrapping.

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