Fundamentals of Multivariate Modeling (Spring 2018; EPSY 905; KU)

Course Information

Brief Course Description

In this course, contemporary approaches to multivariate analysis using mixed-effects models estimated with maximum likelihood and Bayesian methods are presented. Classical topics in multivariate analysis including multivariate analysis of variance and exploratory factor analysis, are covered in the context of mixed-effects models, preparing students for subsequent courses and research that use such model-based methods. Topics include extensions of linear models (regression and analysis of variance) for non-normal data with link functions, introductory matrix algebra, missing data modeling techniques, models for repeated measures data, and path analysis models for multivariate regression evaluating both moderation and mediation effects.

The course will use the R statistical package with R Studio and a set of packages including the EPSY905R Package (Templin, 2018) for all computational and data analysis work involved in the course.

For all other specific information regarding general course policies, course evaluation rubrics, and grading systems, please see the course syllabus at the link below.

Tentatively, the course will be held in a flipped format. Students will watch lecture videos during the week before class. Class time will be spent with Q & A about the video contents and then an exercise relating to the topic or homework using R.

All readings will be made available via campus OneDrive shared folder. Please email me for an invitation to this folder.

Course Materials

16 Jan: Introduction to R

Videos to Watch Prior to Lecture

None

Quizzes To Take Before Class:

None

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

23 Jan: General Linear Models

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Hoffman (2015), Chapter 2

Quizzes To Take Before Class:

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

30 Jan: Interactions in GLMs

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Hoffman (2015), Chapter 2

Quizzes To Take Before Class:

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

06 Feb: Interactions, Continued

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • None

Quizzes To Take Before Class:

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

13 Feb: Distributions and Estimation

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Kutner et al. (2005): Appendix A and Ch. 1
  • Enders (2010): Ch. 3

Quizzes To Take Before Class:

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

  • None

20 Feb: Generalized Linear Models

Videos to Watch Prior to Lecture

  • Introduction to Generalized Linear Models: https://youtu.be/TCEIuqZaEg8
  • Note: watch until 57 minutes in…then move to lecture video below.

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Enders (2010) ch. 3 (ML)
  • Azen and Walker (2011) chs. 2 & 6 (GLMs)
  • Atkins and Gallop (2007)
  • Cohen, Cohen, West, and Aiken (2002)

Quizzes To Take Before Class:

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

13 Mar: Matrix Algebra and MVN

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • Johnson & Wichern (2002) chs. 2, 3, and 4.

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

  • Forthcoming after class

Active Homework Assignments

27 Mar: Multivariate Linear Models

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • None

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

03 Apr: Path Analysis

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Kline (2005) chs. 5, 6

Quizzes To Take Before Class:

In-Class Lecture Materials:

  • None

In-Class Lecture Videos:

Active Homework Assignments

10 Apr: Mixed Models

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • None

Quizzes To Take Before Class:

In-Class Lecture Materials:

  • None

In-Class Lecture Videos:

Active Homework Assignments

17 Apr: Repeated Measures

Videos to Watch Prior to Lecture

Slides and Files From Videos

Optional Readings on Class OneDrive Folder:

  • Maxwell & Delaney (2004) ch. 12-15
  • Wright (1998; shows how Mixed Models can give MANOVA test statistics)

Quizzes To Take Before Class:

In-Class Lecture Materials:

  • None

In-Class Lecture Videos:

  • None (no class)

Active Homework Assignments

24 Apr: Bayesian and MCMC

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • None

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

  • Forthcoming after class

Active Homework Assignments

  • None

Extra Content: Missing Data and MI

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • Enders (2010), Ch. 4, 7, 8, 9

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

  • None

Extra Content: PCA and EFA

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • Johnson & Wichern (2002), Chs. 8 & 9

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

Extra Content: Classification and Clustering

Videos to Watch Prior to Lecture

  • None

Slides and Files From Videos

  • None

Optional Readings on Class OneDrive Folder:

  • Vermunt & Magidson (2002)
  • McCutcheon (2002)

Quizzes To Take Before Class:

  • None

In-Class Lecture Materials:

In-Class Lecture Videos:

Active Homework Assignments

  • None

Homework Schedule

Note: All homework assignments are due at 11:59pm of the date noted below.