A Primer: Factor Analysis & Item Response Theory
(due to requests and demand, the content in this measurement workshop has slightly changed)
Dr. Matthew Diemer, University of Michigan
June 3 & June 4, 2019 - Days 1-2 will involve lectures and planned exercises, divided into four sessions. Participants are encouraged to bring their own data to apply the techniques we are learning during the ‘hands on’ portion of each session. Alternatively, participants will be provided with a dataset and analytic problems to solve.
Both days are anticipated to run from 9am-4pm with a 1hr break for lunch.
Trainees (students and post-docs) - $500
Professionals (including faculty) - $750
NOTE: If also registering for Introduction to Structural Equation Modeling, a 20% fee reduction will be applied to both registrations.
Factor analysis and item response theory (IRT) are complex and powerful tools. Yet, learning to understand and use these approaches can be straightforward. This introductory workshop will emphasize conceptual understanding as well as “hands-on” practice conducting, and interpreting, analyses – with only minimal use of notation and equations.
Attendees will learn how to (a) calculate and interpret common ways to estimate reliability, such as Cronbach’s Alpha and inter-item correlations, (b) how to conduct and interpret exploratory factor analyses (EFA), (c) how to conduct and interpret confirmatory factor analyses (CFA) and (d) how to conduct and interpret item response theory (IRT) models.
These are key competencies to design assessments, evaluate, select, and use commercially or publicly available assessments, and interpret claims about the measurement properties of these assessments. This workshop aims to provide the necessary foundation to make more informed decisions about developing, selecting, evaluating, and interpreting assessments in educational and other settings.
Syntax will be provided for example models in Mplus. I require downloading the free demo version of Mplus (www.statmodel.com) prior to the start of the course, which we will use during the ‘hands on’ portion of each session. Attendees should have a copy of SPSS, Stata, R or some other package that they are familiar with, for (minimal) data manipulation.