Office hours Mondays 2-3 in room 9080, 700 University Ave.
Note: This page is under construction, and will be updated frequently throughout the term.
Link to the projects page works now. Sorry about that!
Last slide show (about the acyclic model, etc.) is posted.
Sagemath code is updated and re-posted again. This is the final version.
Also, I fixed a problem in the sem package. If you have a local version, you might want to download it again from http://www.utstat.toronto.edu/brunner/openSEM/sage/sem.sage.
- Syllabus
- Projects
- Draft Textbook: Structural Equation Models: An Open Textbook (Edition 0.10) by Jerry Brunner.
- August 25, 2022 version
- Website: This includes the LaTeX source and graphics files as well as a pdf version. Last posted August 19, 2022.
- Assignments
- Assignment 1: Quiz on Monday Sept. 26th
- Assignment 2: Quiz on Monday Oct. 17th
- Assignment 3: Quiz on Monday Oct. 31st
- Assignment 4: Quiz on Monday November 14th
- Assignment 5: Quiz on Monday November 28th
- Lecture Notes and Overheads
- Introduction
- PDF LaTeX source code Download zip archive including graphics files
- Random explanatory variables in regression
- Ignoring measurement error in regression: Part 1
- Introduction: PDF LaTeX source code Download zip archive
- A little simulation study
- A big simulation study PDF LaTeX source code Download zip archive
- Large-sample tools
- Ignoring measurement error in regression: Part 2
- Random Vectors
- First try at including measurement error in the regression model
- Double Measurement Regression
- Little Double Measurement Regression Example with lavaan
- BMI Health Study with lavaan
- The General Structural Equation Model
- Brand Awareness Example with lavaan
- Exploratory Factor Analysis
- Confirmatory Factor Analysis Part One
- Confirmatory Factor Analysis Part Two
- Sagemath symbolic math software: Final version
- Latent model rules (especially the acyclic rule)
- Introduction
- R Software
- Official R website, including download links and instructions.
- Introduction to R: A very nice 100-page PDF document. Highly recommended if you are going to be using R for serious work. You don't really need it for this class.
All course materials prepared by Jerry (lecture notes and overheads, homework problems, etc.) are licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Source code is available.