Ken Fujimoto : Introduction to Item Response Theory and Differential Item Functioning I

Posted by Ryan Martin , part of the Graduate Statistics Seminar.

At

April 8, 2014, 3:30 p.m.

In

SEO 636

Abstract

I will introduce the basic theory and assumptions of the 1-parameter, 2-parameter, and 3-parameter logistic item response (IRT) models and a Markov chain Monte Carlo algorithm used to estimate the parameters of an IRT model. These measurement models are frequently used to analyze test data, such as the data arising from the GRE, MCAT, GMAT, and ACT tests. IRT models establish a mathematical relationship between a person's ability level and the technical properties of an item (e.g., item difficulty, discrimination level, and/or guessing).