Many-Facet Rasch Measurement
This course will teach you the analysis and interpretation of judge-intermediated ratings, like essay grading, Olympic ice-skating, therapist ratings of patient behavior, etc.
Overview
This course is intended for researchers and analysts who deal with data that include ratings from human judges. You will learn how to assess whether raters function (as desired) interchangeably, or if they differ systematically in ways that can impair the overall rating system.
- Intermediate, Advanced
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
Students who complete this course will learn basic concepts of software installation and operation required for Rasch measurements. You will explore fit analysis and measurement models, how to account for estimations and interactions, and anchoring.
- Define facets, elements, persons, items, raters in the Rasch context
- Conduct two-facet and three-facet analyses
- Deal with missing data and bias
- Handle interactions with dummy facets
- Detect subsets and determine remedies
Who Should Take This Course
Researchers and analysts in education, psychology, medicine and other fields who deal with data that include ratings from human judges.
Our Instructors
Course Syllabus
Week 1
Software Operation and Basic Concepts
- Software installation and operation
- Facets, elements, persons, items, raters
- Data entry methods, including using Excel
- Rasch measurement concepts
- Dichotomous and polytomous models
- Rasch measures and measurement rulers
Week 2
Fit Analysis and Measurement Models
- A two-facet dichotomous analysis
- Observations, measures, expectations and residuals
- Mean-square and standardized fit statistics
- Outfit and Infit statistics
- A three-facet polytomous analysis
- Reliability, separation and inter-rater reliability
- Rating scale structures
Week 3
Estimation and Interactions
- A four-facet polytomous analysis
- Missing data
- Bias/interaction analysis
- Graphing interactions with Excel
- Recoding the data
- Interactions with dummy facets
Week 4
Anchoring
- Subset detection and remedies
- Anchoring, linking and equating
- Judging plan and Generalizability Theory
- Prettifying output for communication
Class Dates
2022
Instructors:
2023
Instructors:
2024
Instructors:
Prerequisites
Ability to use Microsoft Excel.
The Statistics.com courses have helped me a lot, pushing me to the limit and making me learn much more than I expected I could. The knowledge I gained I could immediately leverage in my job … then eventually led to landing a job in my dream company – Amazon.
Karolis Urbonas
This program has been a life and work game changer for me. Within 2 weeks of taking this class, I was able to produce far more than I ever had before.
Susan Kamp
The material covered in the Analytics for Data Science Certificate will be indispensable in my work. I can’t wait to take other courses. Great work!
Stephen McAllister
I learned more in the past 6 weeks than I did taking a full semester of statistics in college, and 10 weeks of statistics in graduate school. Seriously.
Amir Aminimanizani
This is the best online course I have ever taken. Very well prepared. Covers a lot of real-life problems. Good job, thank you very much!
Elena Rose
The more courses I take at Statistics.com, the more appreciation I have for the smart approach, quality of instructors, assistants, admin and program. Well done!
Leonardo Nagata
This course greatly benefited me because I am interested in working in AI. It has given me solid foundational knowledge…After completing this last course, I feel I have gained valuable skills that will enhance my employability in Data Science, opening up diverse career opportunities.
Richard Jackson
Frequently Asked Questions
-
What is your satisfaction guarantee and how does it work?
-
Can I transfer or withdraw from a course?
-
Who are the instructors at Statistics.com?
Visit our knowledge base and learn more.
Additional Information
Homework
Homework in this course consists of short answer questions to test concepts.
In addition to assigned readings, this course also has supplemental readings available online and an end of course data modeling project.
Course Text
Instructional material will be provided online by the instructor. A reference work is Many-Facet Rasch Measurement (MESA Press, 1994) from www.rasch.org/books.htm
Software
The course will use a time-limited version of Facets software available when the course starts. Microsoft Excel is used extensively. NOTE: Facets does not run on native Macintosh OS; you will need to be running Windows.