EH382-7-SU-CO:
Scaling Methods and Ideal Point Estimation for Surveys and Behaviour
2022/23
Essex Summer School in Social Science Data Analysis
Colchester Campus
Summer
Postgraduate: Level 7
Current
Monday 24 April 2023
Friday 30 June 2023
30
03 February 2023
Requisites for this module
(none)
(none)
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This course focuses on methods to discover, understand and visualize latent patterns in data and is especially suited to students with projects using survey data and other forms of relational data used in political science, sociology, economics, business, marketing, and psychology. The course introduces students to measurement theory and methods of scaling techniques, integrating Multidimensional Scaling, Item Response Theory, and Ideal Point Estimation. The first part of the course will provide an overview of the foundations of these techniques and introduce students to the most common methods for scaling and "spatial" analysis and the visualization of latent patterns in survey and behaviour data.
No information available.
Students will learn to use various computational methods to generate measures of ideology and preferences and understand the latent dimensional properties of social science data, including surveys and legislative data. Students will understand the theories behind these methods and the relationships between Item Response Theory, Ideal Point Estimation and other scaling methods. As these techniques are fundamental parts of much recent work in social science, students will be able to both understand and produce this research based on measuring concepts in this way. In addition, students will be able to:
Understand the fundamentals of measurement theory and scaling techniques,
Explain the advantages and limitations of various scaling techniques
Demonstrate proficiency in using relevant software packages in R
Identify appropriate methods of measurement for a given set of data.
Analyse the results of measurement techniques and present them visually.
Course Prerequisites
The course is designed to be accessible to social science graduate students of all backgrounds. However, students familiar with the R programming environment will find it easier to adapt to course content and assignments, so it is recommended to become familiar with the basic structure of the R syntax and the Rstudio software prior to enrolling. The 1-day Introduction to R offered the Sunday before the first day of class at ESS is recommended for this purpose. In addition, the course assumes some basic familiarity with general statistics (OLS and MLE).
Reading:
Armstrong, D. A., Bakker, R., Carroll, R., Hare, C., Poole, K. T., & Rosenthal, H. (2020). Analyzing Spatial Models of Choice and Judgment (2nd ed). : CRC Press ISBN 9780367612542 – (this text will be provided by ESS).
Module information will be made available at https://essexsummerschool.com/.
Please contact essexsummerschoolssda@essex.ac.uk and govpgquery@essex.ac.uk with any queries.
No information available.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Assessment one |
|
50% |
| Coursework |
Assessment two |
|
50% |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
No
No
No
Available via Moodle
No lecture recording information available for this module.
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