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: TBA
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
Read Enders (2022) Chapter 1 28 Jan
Complete Reading Assessment 1 (in ICON) 28 Jan

Remaining Schedule (Tentative)

Week Date Topic Reading
1 22 Jan Introduction to Class None
2 29 Jan Introduction to Missing Data Chapter 1
3 5 Feb Maximum Likelihood Estimation Chapter 2
4 12 Feb Maximum Likelihood Estimation with Missing Data Chapter 3
5 19 Feb Bayesian Estimation Chapter 4
6 26 Feb Bayesian Estimation with Missing Data Chapter 5
7 5 Mar Bayesian Estimation for Categorical Variables Chapter 6
8 12 Mar Multiple Imputation Chapter 7
9 19 Mar Spring Break: No Class No Readings
10 26 Mar Multilevel Missing Data Chapter 8
11 2 Apr Missing Not at Random Processes Chapter 9
12 9 Apr Special Topics and Applications Chapter 10
13 16 Apr Guidance for Working with Missing Data Chapter 11
14 23 Apr Missing Data in Psychometric Models: Latent Variable Scores Mislevy et al. (1992)
15 30 Apr No Class: AERA/NCME Conference
16 7 May Missing Data in Psychometric Models: Implications for CAT Doebler et al. (2013); Jewsbury et al. (2024);