Item Response Theory Training Seminar

Item Response Theory Seminar

An introductory 3-day course introducing item response theory measurement models applied to psychological and educational data.

Over the last 30 years Item Response Theory (IRT) has essentially replaced traditional classical test theory approaches to designing, evaluating, and scoring large-scale tests of cognitive ability.  More recently, IRT measurement models have been increasingly used to better assess health outcomes, personality traits, and psychopathology.  In this course we review the most popular unidimensional IRT models for dichotomous and polytomous item response data.  Multidimensional IRT models, in particular the bifactor model and its applications, will also be reviewed.  The assumptions underlying IRT models, and how to evaluate them, as well as methods of establishing model to data fit will be covered extensively.  Finally, we will examine  the major applications of IRT including scale construction, evaluating differential item functioning, and computerized adaptive testing. The primary software used in the course are the mirt and psych libraries available in R.  Each day will include software demonstrations.

Participants will receive an electronic copy of all course materials, including lecture slides, practice datasets, software scripts, relevant supporting documentation, and recommended readings. Participants will also have access to a video recording of the course.

Fall Camp: September 14 – 16, 2017
Brea, CA – Embassy Suites North Orange County


FAQVenue InfoHotel Reservations

Topics include:

  • Unidimensional IRT models for dichotomous and polytomous item response data
  • Multidimensional IRT models, including the bifactor model
  • Testing model assumptions and fit
  • Popular applications of IRT models, including the assessment of differential item functioning, person fit, and computerized adaptive testing.

Note: Due to time constraints, this course will not focus include discussion of the technical details underlying marginal maximum likelihood estimation of item parameters or Bayesian estimation approaches.

Payment Options

$1,095 Faculty/Professional or $945 Student/Post-Doc


Learning Objectives

After engaging in this 3-day statistics training institute course lectures and discussions as well as completing the hands-on practice activities with real data, participants will be able to:

  • Understand the critical differences between IRT and classical test theory, and what the relative advantages of IRT are.
  • Fit any IRT model to their own data using freely available software.
  • Test the assumptions underlying application of IRT models, understand the consquences of violating those assumptions, and ultimately, evaluate the fit of IRT models to their own data.
  • Understand the important link between factor analysis and item response theory.
  • Gain a basic understanding of IRT applications, and the abilitiy to evaluate such applications in their own data.

Course Syllabus

Thursday September 14, 2017
9:00-9:30 Welcome and introductions
9:30-10:45 Item Response Theory Basics
10:45-11:00 Snack and refreshment break
11:00-12:30 Unidimensional Dichotomous IRT Models

1, 2, 3, and 4 parameter models

12:30-1:30 Lunch break
1:30-3:00 Unidimensional Polytomous IRT Models: Graded Response Model
3:00-3:15 Snack and refreshment break
3:15-5:00 Unidimensional Polytomous IRT Models:

Generalized Partial Credit; Partial Credit; Nominal Response Model

Friday September 15, 2017
9:00-10:45 Overview of Multidimensional IRT Models
10:45-11:00 Snack and refreshment break
11:00-12:30 Bifactor Models and Applications
12:30-1:30 Lunch break
1:30-3:00 Evaluating IRT Model Assumptions and Assessing Fit 1
3:00-3:15 Snack and refreshment break
3:15-5:00 Software Demonstrations; Individual Consultations
Saturday September 16, 2017
9:00-10:45 Evaluating IRT Model Assumptions and Assessing Fit 2
10:45-11:00 Snack and refreshment break
11:00-12:30 Applications of IRT models: scoring, CAT, person-fit
12:30-1:30 Lunch break
1:30-3:00 Applications of IRT models: Linking DIF
3:00-3:15 Snack and refreshment break
3:15-5:00 Software Demonstrations; Individual Consultations

Prerequisites

Required:

  • Intermediate proficiency in basic statistical theory as would be gained in a 1st year graduate course.
  • Limited experience in statistical software such as R command language and libraries.

Not required but advantageous:

  • At least limited experience (e.g., graduate-level course) with classical measurement theory and concepts.

No level of proficiency beyond basic awareness is assumed for skills related to:

  • Advanced mathematical or statistical topics such as matrix algebra.

Instructor: Steve Reise Ph.D.

Item Response Theory Statistics Training Course

Dr. Reise received his Ph.D. from the Department of Psychology at the University of Minnesota in 1990. He is presently full professor at UCLA in Quantitative Psychology. His research addresses the application of item response theory measurement models to personality, psychopathology and health outcomes scales. Current interests include robust model comparison and person-fit assessment in structural equation models, and alternative item response theory models for handling non-normal or unipolar traits.

Software and Computer Support

Participants need to bring a laptop computer with Wi-Fi capabilities.

All statistical software used at Stats Camp will be available, free to participants, on our SMORS (statistical modeling on remote servers) system for the duration of camp.

Instruction will be provided for the methods using libraries available in the R statistics package.  R is a freeware software and a list of libraries to download will be provided before the course.

Course Files

Below are links to course files for those who enrolled in the course. Please download these files onto your computer on the first day of the course. The files are password protected to respect the intellectual property rights of the instructors. By using your login information, you agree not to share your login information or the content protected by it.

Course files and downloads will be posted on the first day of class.

Statisics CoursesWhy Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Course Resources
  • Breakfast (Embassy guests), Lunches, & Snacks Daily