**Lecture notes**: 1up PDF; 4up PDF**Lab exercise**: Exercise 1

Setting the stage: EFA, CFA, SEM, Path analysis

- Goal: Understand relations among a large number of observed variables
- Goal: Extend regression methods to (a) multiple outcomes, (b) latent variables, (c) accounting for measurement error or unreliability
- Thinking: Equations -> Path diagram -> estimate, test, visualize

**Lecture notes**: 1up PDF; 4up PDF**Examples**:- Essay scoring data: congeneric, tau-equiv and parallel models R code, for sem package; Results: votaw.html

**Lab exercise**: Exercise 2- Data set: CSV file; SPSS SAV file
- R code: lavaan models
- AMOS file

- Effects of measurement error
- Testing equivalence of measures with CFA
- Multi-factor, higher-order models
- Multi-group models: Factorial invariance

- CFA in lavaan. A nice tutorial on fitting CFA models using
`lavaan`

. It uses a larger version of the Holzinger-Swineford (1939) data used in the exercise and discusses goodness-of-fit measures, model comparison, and R tools to get nice output for write-ups.

**Lecture notes**: 1up PDF; 4up PDF**Examples**:- Health care utilization R code, for lavaan package; Results: healthutil1.html
- Wheaton et al. Stability of Alienation R code, for sem package; Results: wheaton.html

- The full SEM model
- Longitudinal data
- Power & sample size
- SEM extensions

Copyright © 2019 Michael Friendly. All rights reserved.

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