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Item Response Theory Training Course

Item Response Theory

June 26, 2023 @ 5:00 pm - June 30, 2023 @ 9:00 pm CDT

| $945.00 – $1,295.00

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Statistics Training Course Offerings

Statistical Methods Training Courses
LIVE STREAM – 5-day Statistics Short Course

Seminar Overview:

A 5-day course in the theory and application of item response theory. As a prerequisite, participants should be proficient in the material covered in a one-semester graduate-level psychometrics course or an equivalent level of knowledge from professional experience in test development.

Seminar Topics:

  • Foundations, principles, and evolution of IRT
  • The relationship between measurement, classical test theory, IRT, and factor analysis
  • Linking terms and concepts in IRT, factor analysis, and classical test theory
  • Assumptions of IRT models and their evaluation – test dimensionality and local independence
  • The principle and implications of IRT model invariance
  • Types of IRT models – model selection relative to test/instrument development and utility
  • Unidimensional and multidimensional IRT
  • Estimation of item parameters and person’s ability or latent traits
  • Item and test information – definition, application, and implications for test development
  • IRT-based test and instrument construction, evaluation, and refinement
  • Steps in conducting an IRT analysis in relation to the testing problem
  • Interpreting IRT output to inform test refinement
  • Identification of potentially biased items and tests – techniques and practical solutions
  • Introduction to longitudinal IRT
  • Software used for conducting IRT analyses for a variety of models

Seminar Description:

Item response theory (IRT), also known as modern test theory, is a system of modeling procedures that uses latent characteristics of persons or examinees and test items as predictors of observed responses (de Ayala, 2022; Price, 2016; Lord, 1980). IRT is a model-based theory of statistical estimation that conveniently places persons and items on the same metric based on the probability of response outcomes. IRT offers a powerful statistical framework that is useful for experts in disciplines such as cognitive psychology, education, psychiatry, or social/developmental psychology when the goal is to construct explanatory models of behavior and/or performance in relation to theory. 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.

Instructor: Larry Price, Ph.D.

Larry Price, Ph.d. is a Professor of Psychometrics & Statistics and Director of the Office of Data Analytics & Methodology at Texas State University. Between 1999 and 2002, Dr. Price was employed at The Psychological Corporation in San Antonio as a Senior … Psychometrician/Statistician where his work focused on improving the psychometric properties of the Wechsler Scales of Intelligence Memory (e.g., WISC-III, WISC-IV, WAIS-III, WMS-III, and WPPSI-III), and Achievement (WIAT-II) and other psychological measures such as the Beck Depression Inventory (BDI) and Clinical Evaluation of Language Fundamentals (CELF-IV). His research interest includes the theoretical development and testing of Bayesian and non-Bayesian psychometric models in psychological and neuropsychological research (neuroimaging network analysis), theoretical development, testing, and refinement of classical and modern psychometric methods in the behavioral sciences, development of dynamic multivariate time series models for the psychological, social and neurosciences. Prior to working at Psychological Corporation, he worked at Emory University from 1986 to 1999 as a Biostatistician and Psychometrician in the School of Medicine. Funding mechanisms for Dr. Price’s work include NIH, NSF, DOE, and private organizations.

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APA Continuing Education Credits:

This course offers 18hrs of credit hours for continuing education. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content.

Seminar Includes:

Materials, downloads, recorded course video viewable for up to one year.

Learning Objectives:

  • Acquire a basic understanding of the role of IRT as applied to psychological measurement, test development, refinement, and evaluation in the social and behavioral sciences.
  • Develop an understanding of the conceptual and theoretical basis of IRT approaches to psychometrics.
  • Conceptualization and estimation of reliability.
  • The role of validity in IRT in comparison to classical test theory.
  • Acquire knowledge of IRT models used for item response data acquired as dichotomous, polytomous, and nominal.
  • Acquire knowledge of how to properly apply IRT principles and techniques in test development, and item analysis/refinement.
  • Gain knowledge of how to assess requisite assumptions of IRT including dimensionality, invariance, and local item independence.
  • Gain knowledge of how to estimate and report conditional or person-specific reliability using IRT latent trait information.
  • Gain knowledge of how to use IRT models for detecting differential functioning of items and tests (a.k.a. model invariance in factor analysis and structural equation modeling).
  • Acquire knowledge of how to use IRT for test equating and norms development.

Seminar Prerequisites:

Required:

  • Intermediate proficiency in psychometric methods and/or theory in a graduate course.

Not required but advantageous:

  • Limited experience (e.g., graduate-level course) in probability and mathematical statistics.

Software and Computer Support:

Students must have access to R Studio and the R MIRT package installed. For computer practice, students will primarily use the R MIRT package. Examples will also be presented using IRTPRO or flex MIRT available from Vector Psychometric Group (https://store.vpgcentral.com).

To facilitate learning, examples in the course will draw primarily on those included in the book Handbook of Educational Measurement and Psychometrics Using R. It is recommended that participants have access to this book during the course. A companion site for the book that includes R code and sample data by chapter is available at: (http://bit.ly/hemp_code). Examples will also use intelligence test data provided from Psychometric Methods: Theory into Practice, by the course instructor.

Day 1  
5:00-5:30 Welcome and introductions
5:30-6:30 Foundations, principles, and current practice of IRT in testing research, and development.  The relationship between measurement, classical test theory, IRT, and factor analysis.

 
6:30-6:45 Break
6:30-7:45 Linking terms and concepts in IRT, factor analysis, and classical test theory with implications for practical IRT use. The role of reliability and validity in relation to modern test theory. Types of unidimensional IRT models (dichotomous, polytomous, nominal), assumptions, and their evaluation. Introduction to software for IRT – MIRT program in R; IRTPRO; flex MIRT.

 

 
7:45-9:00 Introduction and practice with software for IRT – MIRT program in R; IRTPRO; flex MIRT.

 
Day 2
5:00-6:30 Unidimensional IRT dichotomous response model – estimation of item parameters, model fit, person’s ability/latent traits, and interpreting the output Computer exercise with example data.

 
6:30-6:45 Break
6:45-7:45 Unidimensional IRT polytomous and nominal response models – estimation of item parameters, model fit, person’s ability/latent traits, and interpreting the output. Computer exercise with example data.

 
7:45-9:00 Using IRT results to inform test development practice, refinement, and decision-making. IRT-based conditional and test reliability estimation, use, and reporting
Day 3  
5:00-6:30 Introduction to multidimensional IRT (MIRT) – theory and practical application examples. Overview and advantages of fully Bayesian IRT/MIRT.
6:30-6:45 Break
6:45-8:00 Software applications for MIRT analysis, including interpretation of the output.
8:00-9:00 Using IRT results to inform test development practice, refinement, and decision-making.
Day 4
5:00-6:30 Detecting functioning of items and tests (a.k.a. model invariance in factor analysis and structural equation modeling).

 
6:30-6:45 Break
6:45-8:00 Computer practice for conducting differential item and test functioning, including interpretation of output and reporting results.
8:00-9:00 Continuation of practice for conducting differential item and test functioning, including interpretation of output and reporting results.
Day 5
5:00-6:30 Introduction to test score equating and linking. Using IRT for equating different forms of tests.
6:30-6:45 Break
6:45-9:00 Time for addressing student-specific questions and needs to enhance learning. Additional practice using IRT programs and interpretation of results.

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