PSMB060 Experiment and analysis of discrete choices in applied psychology

Faculty of Arts
Spring 2022

The course is not taught in Spring 2022

Extent and Intensity
1/1/0. 3 credit(s). Type of Completion: k (colloquium).
Taught in person.
Teacher(s)
Mgr. Michal Šimeček, Ph.D. (lecturer), PhDr. Zuzana Slováčková, Ph.D. (deputy)
Guaranteed by
Mgr. Michal Šimeček, Ph.D.
Department of Psychology – Faculty of Arts
Contact Person: Jarmila Valchářová
Supplier department: Department of Psychology – Faculty of Arts
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 30 student(s).
Current registration and enrolment status: enrolled: 0/30, only registered: 0/30
fields of study / plans the course is directly associated with
Course objectives
Discrete choice research is widely used in many areas of applied science. Although this approach was developed to describe decision-making in economics, it has spread to many other disciplines, such as political science, marketing, health care, or environmental studies. Decision theory is also widely used in transport research and modeling (Ben-Akiva & Lerman, 1985). The first part of the course will introduce research on preferences, discrete choice experiments and analysis of results (Henscher et al., 2007). In the second part, a joint experiment will be designed, which the participants administer, and in the third part of the course, the results will be jointly analyzed and interpreted in the R environment (Croissant, 2012). At the end of the course, the participant will be aware of the possibilities of research of preferences in various fields and will be able to design and analyze a simple experiment of discrete choices.
Learning outcomes
At the end of the course, the participant will be aware of the possibilities of research of preferences in various fields and will be able to design and analyze a simple experiment of discrete choices.
Syllabus
  • 1. Introduction to discrete choice experiment and decision analysis
  • - What can DCE be used for in various fields - research of preferences in marketing, transport, medicine, valuation of public goods and public policies.
  • - Data sources - Revealed Preferences (RP), experimental approaches (DCE), advantages and limitations.
  • - Construction of the sample - probabilistic, quota, choice-based sample (CBS).
  • - Discrete Choice Analysis (DCA) - decision models (multinomial logit, mixed logit, nested models, heteroskedastic models).
  • - Outputs of the analysis - determining the willingness to pay (WTP) and willingness to accept (WTA), elasticity, demand forecast (preference).
  • 2. Preparation of the experiment - together with the course participants we will choose a research topic.
  • - Select a topic
  • - Creating alternatives
  • - Creating attributes
  • - Preparation of experimental design
  • - Implementation of the experiment - will take place in a random (or survey) manner using the CAWI or PAPI method.
  • 3. Decision analysis
  • - The analysis will be shown in the R environment (mlogit package).
  • - Parameters will be estimated on a simple multinomial model by type according to the selected experimental design
Teaching methods
lectures, class discussion, group project
Assessment methods
Active participation on group project.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2021.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2022/PSMB060