Multidimensional Measurement Models (Fall 2023)

This repo contains course materials for the Multidimensional Measurement Models course, given during the fall semester of 2023 at the University of Iowa (PSQF 7375) by Jonathan Templin.

Course Information

Instructor:	Jonathan Templin
email:	jonathan-templin@uiowa.edu
Syllabus:	Syllabus Link
Course website:	Course Website Link
Course repo:	GitHub Repo
Lecture videos:	YouTube Playlist
Office:	S210B Lindquist Center
Office Phone:	319-335-6429
Classroom:	S210A Lindquist Center
Course Meeting Time:	W 12:30-15:20
Course Office Hours:	F 09:00-11:00 or by appointment

Course Schedule

Week 1: August 23, 2023: Introduction; What is Dimensionality; Estimation Toolbox

• Read prior to class:
  • Course Syllabus
• Lecture slides:
  • https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/blob/main/materials/Week%2001/mmm2023_lecture01_intro.pdf
  • Lecture Videos:
    • Part 1: https://youtu.be/81B4bYhLi-o
    • Part 2: https://youtu.be/PuqfqScaFyo; Note, audio only after about 5 minutes.
• Coding activity: Introduction to High Performance Computing and Argon
  • HPC Argon Wiki
  • Slides:
    • https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/blob/main/materials/Week01/mmm2023_lecture01_hpc.pdf
  • Computing Setup:
    • Visual Studio Code (with Extensions)
    • R (via Rig)
    • Mounting Argon Drives Locally
  • Example Job Submissions
    • https://jonathantemplin.com/introduction-to-the-university-of-iowa-high-performance-computing-system-argon-and-iowa-interactive-data-analytics-service-idas/

Week 2, August 30, 2023: Argon

• Read prior to class: Nothing

• Lecture handout:

  • https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/blob/main/materials/Week02/mmm2023_argon.md

• Lecture Videos https://youtu.be/U9I2U9neYTE

• Useful Links

  • Argon Wiki: https://wiki.uiowa.edu/display/hpcdocs/HPC+Documentation+Home
  • Notebooks Site: https://notebooks.hpc.uiowa.edu/
  • Jonathan's awesome Argon guide: https://jonathantemplin.com/introduction-to-the-university-of-iowa-high-performance-computing-system-argon-and-iowa-interactive-data-analytics-service-idas/

• Formative Assessment 1 Assigned (Due 09/05/2023)--on ICON

Week 3: September 6, 2023: Psychometric Prerequisites (Generalized Models, IRT, Structural vs. Measurement Models, Basic MIRT Models)

• Read prior to class (note: readings are on ICON):

  • For discussion: Chapter 1: Bartholomew, Knott, and Moustaki (2011)
  • For reference: Chapter 2: Reckase (2009)

• Links to Lecture Materials:

  • Lecture Slides: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week03/03_Psychometric_Prerequisites.html#/title-slide
  • Lecture Video: https://youtu.be/ksK3-bvMKn4
  • Lecture Handout (Same content as slides, but in DOCX format): https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week03/03_Psychometric_Prerequisites_Handout.docx
  • Coding Activity: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/blob/main/materials/Week03/03_Coding_Activity.md
    • My Coding Activity File: https://raw.githubusercontent.com/jonathantemplin/MultidimensionalMeasurementModels2023/main/materials/Week03/03_classSimulation.R

• Formative Assessment 2 Assigned (Due 09/12/2023)--on ICON

Week 4: September 13, 2023: Model Fit

• Homework 1 Due 09/12/2023 ICON:

  • Note: Your personal data set is on Argon (see ICON for details)

• Read prior to class (note: readings are on ICON):

  • Cai, L., Maydeu-Olivares, A., Coffman, D.L. and Thissen, D. (2006), Limited-information goodness-of-fit testing of item response theory models for sparse 2P tables. British Journal of Mathematical and Statistical Psychology, 59: 173-194. https://doi-org.proxy.lib.uiowa.edu/10.1348/000711005X66419

• Links to Lecture Materials:

  • Lecture Slides: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week04/04_Model_Fit.html#/title-slide
  • Lecture Handout (Same content as slides, but in DOCX format): https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week04/04_Model_Fit_Handout.docx
  • Lecture Videos:
    • Part 1: https://youtu.be/ojufSzYIBTA
    • Part 2: https://youtu.be/AwDcNQ31ca8
  • Coding Activity: None this week

• Homework 2 Due 09/27/2023 ICON

Week 5: September 20, 2023: Multidimensional Difficulties (Identifiability, empirical identification, quantifying dimensionality)

• Read Prior to Class: Torres Irribarra & Arneson (2023) on ICON
• Formative Assessment 4 Assigned (Due 09/26/2023)--on ICON
• Links to Lecture Materials:
  • Lecture Slides: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week05/05_Difficulties.html
  • Lecture Handout (Same content as slides, but in DOCX format): https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week05/05_Difficulties_Handout.docx
  • Lecture Video: https://youtu.be/-05XICYqnlo
  • Coding Activity: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/blob/main/materials/Week05/05_Coding_Activity.md

Week 6: September 27, 2023: Estimation Methods (Marginal Maximum Likelihood; Limited Information; Bayesian Methods)

• Read Prior to Class: Kaplan (2009), Chapters 2 and 3 (Estimation in MVN models)
• Formative Assessment 5 Assigned (Due 10/03/2023)--on ICON
• Links to Lecture Materials:
  • Lecture Slides: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week06/06_Estimation.html#/title-slide
  • Lecture Handout (Same content as slides, but in DOCX format): https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week06/06_Estimation_Handout.docx
  • Lecture Video: https://youtu.be/8BQ28HqQ0CU
  • Coding Activity: None
• Homework 3 Due 10/11/2023 via ICON
  • Assignment text also available here: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/homework/HW3/HW3.docx

Week 7: October 4, 2023: Full and Limited Estimation Methods (Monte Carlo, EM, MHRM, QN)

• Read Prior to Class: Nothing
• Formative Assessment 6 Assigned (Due 10/10/2023)--on ICON
• Links to Lecture Materials: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/tree/main/materials/Week07
  • Lecture Video: https://youtu.be/lCEt5LR3XPM
• Coding Activity: Work on Homework #3

Week 8: October 11, 2023: Bayesian Estimation Methods (MCMC)

• Watch prior to class (in case you are not familiar with Stan):
  • https://youtu.be/kMH4ifVjyLQ
  • https://youtu.be/YKyPRNLbupI
  • https://youtu.be/pDupeE6W5eI
• Formative Assessment 7 Assigned (Due 10/17/2023)--on ICON
• Links to Lecture Materials: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week08/08_Bayesian_Estimation.html
  • Lecture Video: https://youtu.be/hT-bFyvW33o
• Coding Activity: None

October 18, 2023: No Class

Week 9: October 25, 2023: When Multidimensionality is Considered A Bad Thing

• Read prior to class:
  • Reckase (2009), Chapters 3 and 4
• Formative Assessment 8 Assigned (Due 10/31/2023)--on ICON
• Links to Lecture Materials: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week09/09_Unwanted_Multidimensionality.html
  • Lecture Video: https://youtu.be/4jJF66XdOi0
• Coding Activity: HW4 Work

Week 10: November 1, 2023: Exploratory Mixture Models for Detecting Groups

• Read prior to class:
  • Bartholomew, Knott, and Moustaki (2011), Chapter 6 (via ICON)
• Formative Assessment 9 Assigned (Due 11/07/2023)--on ICON
• Links to Lecture Materials:
  • Slides: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week10/10_Mixture_Models.html#/title-slide
  • Handout: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week10/10_Mixture_Models_Handout.docx
  • Lecture Video: https://youtu.be/lD8ujxcwlx4
  • Analysis files: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/tree/main/materials/Week10
• Homework 5 Assigned: Due 11/14/2023 via ICON
  • Homework text also available here: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/homework/HW5/HW5.docx

Week 11: November 8, 2023: Diagnostic Classification Models/Bayesian Networks

• Read prior to class:
  • Rupp, Templin, and Henson (2009): Chapter 3 (via ICON)
• Formative Assessment 10 Assigned (Due 11/14/2023)--on ICON
• Links to Lecture Materials:
  • Slides: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week11/11_DCMs.pdf
  • Lecture Video: https://youtu.be/soPhTpFwHnM

Week 12: November 15, 2023: Confirmatory Models; Latent Variable Interactions; Models with Specific Purposes (Higher order, bifactor, method factors, extreme response models, scoring approaches)

• Read prior to class:
  • Rupp, Templin, and Henson (2009): Chapters 7 and 8 (via ICON)
• Formative Assessment 11 Assigned (Due 11/28/2023) on ICON
• Links to Lecture Materials:
  • Slides: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week12/12_DCM_Structural_Models.pdf
  • Example Files: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/tree/main/materials/Week12
  • Mplus Script-Building Process: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week11/11_LCDM_Mplus.pdf
  • Mplus Example Files: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week11/11_Mplus_example.zip
  • blatent Example Files: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week11/11_blatent_example.zip
  • Lecture Video: https://youtu.be/tE05opgg3Kk
• Homework 6 Assigned: Due 11/28/2023 via ICON
  • Homework text also available here: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/homework/HW6/HW6.docx

November 22, 2023: No Class (Fall Break)

Week 13: November 29, 2023: On the Use of Test Scores

• Read prior to class: Nothing
• No More Formative Assessments
• Links to Lecture Materials:
  • Slides: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week13/13_On_Scores.pdf
  • R Syntax: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week13/13_On_Scores.R
  • Data Files
    • Binary Data: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week13/9-10th_Grade_Q2.RData
    • Likert Data: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week13/gamblingdata.csv
    • Happiness Data: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week13/happinessData.csv
• Lecture Video: https://youtu.be/p8x6pgDf-Ag

Week 14: December 06, 2023: Subscores and Other Models

• Links to Lecture Materials:
  • Lecture Document: https://jonathantemplin.github.io/MultidimensionalMeasurementModels2023/materials/Week14/14_Subscores_and_Popular_Models.html
  • R Syntax Files:
    • Subscore simulation: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week14/subscoreSame.R
    • Lecture analyses: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week14/14_Subscores_and_Popular_Models.R
  • Data File: https://github.com/jonathantemplin/MultidimensionalMeasurementModels2023/raw/main/materials/Week14/9-10th_grade_q2.RData
• Lecture Video: Unavailable due to technical difficulties.