# Introduction to Item Response Theory (IRT)

This course will teach you the statistical basis for analyzing multiple-choice survey or test data – item response theory (IRT).

## Overview

Complex sample designs such as stratified cluster sampling make it possible to extract maximum information at minimum cost, but they are typically harder to work with than simple random samples. How do you analyze the resulting data – in particular, how do you determine margins of error? This course teaches you how to estimate variances when analyzing survey data from complex samples, and also how to fit linear and logistic regression models to complex sample survey data.

• Introductory
• 4 Weeks
• Expert Instructor
• Tuiton-Back Guarantee
• 100% Online
• TA Support

## Learning Outcomes

After taking this course you should be able to understand how IRT is used, which models are appropriate for different contexts, how to construct scales, and how to understand output from IRT analyses.

• Define traits, items, scales and scores
• Add item parameters: 1-, 2- and 3-Parameter models
• Construct appropriate dichotomous and polytomous scales Interpret scores
• Assess fit, and how well items work

## Who Should Take This Course

Researchers, social scientists, and education measurement scientists who want to learn about analyzing and creating better scales, tests, and questionnaires.

## Our Instructors

#### Dr. Karen Schmidt

Dr. Karen Schmidt is a Professor in The Department of Psychology at The University of Virginia, Charlottesville, VA. Dr. Schmidt has been a professor for 24 years, and teaches courses in statistics, research methods, and item response theory (IRT) and Rasch measurement at the undergraduate and graduate level. Dr. Schmidt specializes in psychometrics, with specific focus on Rasch measurement and item response theory (IRT). Her research and interests include scale and test design and analysis, item features experimental design and analysis, and trait measurement in a wide variety of areas, including psychological, educational, health, and medical sciences.

## Course Syllabus

### Week 1

Introduction, Theory, Concepts

• History of IRT
• Classical test theory and IRT
• Why is effective measurement important?
• Traits, items, scales and scores

### Week 2

Measuring Dichotomous Responses

• Adding item parameters: 1-, 2- and 3-Parameter models
• What do the scores mean?
• Dichotomous scale construction considerations

### Week 3

Measuring Polytomous Responses

• What do the scores mean?
• Polytomous scale construction considerations

### Week 4

Practical Considerations and Applications of IRT

• Assessing fit: How well do the items work?
• Item and scale effectiveness: Dimensionality, Standard Errors, Information
• Differential Item Functioning (DIF) and Computerized Adaptive Testing (CAT)

## Class Dates

### 2024

02/16/2024 to 03/15/2024
Instructors: Dr. Karen Schmidt
08/09/2024 to 09/06/2024
Instructors: Dr. Karen Schmidt

### 2025

02/21/2025 to 03/21/2025
Instructors: Dr. Karen Schmidt
08/08/2025 to 09/05/2025
Instructors: Dr. Karen Schmidt

## Prerequisites

In this course, you will use Excel and R. We recommend using R in conjunction with R Studio. Some familiarity with R is assumed. Exercises and materials will be provided to introduce you to R and R Studio with roughly 3 hours of additional work. Warning: The first week of the course has a comparatively heavy workload of regular course material, so if you are very new to R, be sure to appropriately budget your time.

## Register For This Course

Introduction to Item Response Theory (IRT)

#### Homework

The homework in this course consists of multiple-choice questions on course concepts, ungraded practice exercises using R, and a final project using R.

#### Course Text

Course subject materials will be provided in each lesson. A suggested text (not required), for those who wish a more rigorous review of the concepts, is Fundamentals of Item Response Theory (Measurement Methods for the Social Science) by Ronald K. Hambleton, available on Amazon or on Sage.

#### Software

In this course, you will use Excel and R. We recommend using R in conjunction with R Studio. Some familiarity with R is assumed. Exercises and materials will be provided to introduce you to R and R Studio with roughly 3 hours of additional work. Warning: The first week of the course has a comparatively heavy workload of regular course material, so if you are very new to R, be sure to appropriately budget your time.

#### Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

Chrome

Firefox

Safari

• Navidys (for colorblindness, dyslexia, and reading difficulties)
• HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

## Register For This Course

Introduction to Item Response Theory (IRT)