1 Introduction
1.1 Course Content
EDPY 607 - Measurement Theory II as the second step in the graduate-level measurement sequence (EDPY 507 and EDPY 607) in the Measurement, Evaluation, and Data Science program at the University of Alberta. The main purpose of EDPY 607 is to bring students as close to current practice in educational measurement as possible. On the basis of the concepts, principles, and content presented in EDPY 507, this course will focus on more advanced topics and applications required to develop, administer, and use educational and psychological assessments using the same logical structure as EDPY 507.
I created this online book to provide graduate students taking EDPY 607 with hands-on materials on advanced psychometric analyses in R (R Core Team, 2022). The book includes real and synthetic data examples involving psychometric analysis (both R codes and output). These examples will help you better understand the psychometric theories and concepts that we will discuss in the lectures. The content of this online book has been prepared and deployed using the bookdown package (Xie, 2016) in R (R Core Team, 2022). The course logo has been created by me using the hexSticker package (Yu, 2020).
1.2 Chapters
The chapters of this online book will be based on the following topics:
- Construct Validation
- Factor analytic methods
- Psychometric network analysis (PNA)
- Measurement invariance (factor analytic vs. PNA approaches)
- Advanced IRT Applications
- Explanatory item response modeling
- Multidimensional IRT models
- Digital Testing Applications
- Computerized adaptive testing
- Multistage adaptive testing (with automated test assembly)
- Process data in digital assessments
- Other Topics in Computational Psychometrics (tentative)
- Text mining applications for test development
- Detecting aberrant responses
- Optimization issues in psychometrics (e.g., scale abbreviation)