Missing Data Methods (Spring 2025; University of Iowa: PSQF 7375)

Course Objectives

This course section explores missing data methods in applied statistics, data science, and psychometrics; emphasizing techniques such as multiple imputation, Bayesian methods, and maximum likelihood to handle and analyze incomplete data sets effectively.

Course Readings

The course will follow the chapters of Applied Missing Data Analysis (2nd Edition) by Craig Enders. The University of Iowa Library has electronic access to the book at https://ebookcentral-proquest-com.proxy.lib.uiowa.edu/lib/uiowa/detail.action?docID=7027149. Additional readings will be posted our course ICON site.

Course Details

Instructor:	Jonathan Templin
email:	jonathan-templin@uiowa.edu
Course website:	https://jonathantemplin.github.io/MissingDataMethods2025/
Course repo:	https://github.com/jonathantemplin/MissingDataMethods2025
Course YouTube Playlist:	https://www.youtube.com/watch?v=-YUmmA_akLM&list=PLSmMs4UgmSMgYbH3ryj-BTk7F7WWbgWPO
Office:	S300A Lindquist Center
Office Phone:	319-335-6429
Classroom:	S108 LC
Course Meeting Time:	W 12:30pm-3:20pm
Course Office Hours:	W 10:00am-12:00pm via Zoom at https://uiowa.zoom.us/my/jonathantemplinuiowa
Syllabus:	https://jonathantemplin.github.io/MissingDataMethods2025/s25mdm_syllabus.html

Current Assignments

Assignment	Due Date
Homework #3 (Available in ICON)	28 Mar
Chapter 5 Quiz	01 Apr

Lecture and Class Files and Links

Date	Topic	Materials
22 Jan	Introduction to class	Syllabus Lecture Video
29 Jan	Introduction to Missing Data	Slides (HTML) Slides (PDF) R files Lecture Video
05 Feb	Technical Prerequisites	Slides (PDF) R files Lecture Video
12 Feb	Maximum Likelihood Estimation	Slides (PDF) R files Lecture Video
19 Feb	MLE with Missing Data (and lavaan)	Slides (PDF) R files Lecture Video
26 Feb	No Class
05 Mar	lavaan and Maximum Likelihood Estimation with Missing Data (Chapter 3)	Handout (html) R files Lecture Video
12 Mar	Introduction to Bayesian Methods	Slides (pdf) R files Lecture Video
26 Mar	Bayesian Estimation with Missing Data	Slides (pdf) R files Lecture Video

Remaining Schedule (Tentative)

Week	Date	Topic	Reading
11	2 Apr	Bayesian Estimation with Missing Data and Bayesian Estimation for Categorical Variables	Chapter 5/6
12	9 Apr	Multiple Imputation	Chapter 7
13	16 Apr	Multilevel Missing Data	Chapter 8
14	23 Apr	Missing Not at Random Processes	Chapter 9
15	30 Apr	No Class: AERA/NCME Conference
16	7 May	TBA