Dates & Time:
Kick-Off: November 18, 2019; 6 pm
Seminar: February 10 – 12, 2020; full time (tba)
Exam: February 17, 2020; 9 am
Location:
Universität Hamburg, Moorweidenstr. 18, room 0005.1 (for 18 Nov 2019, 10 – 12 Feb 2020); room for exam tba
Instructor:
Prof. Dr. Karen Gedenk
Teaching Language:
English
Credit Points:
2 SWS/5 LP
Registration:
until November 11, 2019. Please send an e-mail to Elke Thoma (elke.thoma@uni-hamburg.de) which informs about:
- your name
- your email address
- the supervisor of your doctoral thesis and topic
- your background in statistics and empirical research.
Objectives:
This course is designed to lay the foundations of good survey-based research in different areas of Business Administration. Through a critical review of existing literature, presen- tations and discussions, students become acquainted with common problems in survey- based research and advanced methods for solving them. Students get an overview of dif- ferent methods in the survey research “tool box”. This helps them identify appropriate methods for their own research and evaluate research done by others.
Prerequisites:
Students should have a solid foundation in statistics and be familiar with the basics of multivariate data analysis.
Student Evaluation:
To pass the course, participants are required to make a successful presentation. In addi- tion, they need to read one paper on each topic, participate in class discussions, and pass the exam.
Contents & Working Requirements:
Exemplary topics are preference measurement, measurement models for complex con- structs, structural equation models, moderation and mediation, multicollinearity, heter- ogeneity, endogeneity, common method bias. A list of topics and readings will be pro- vided at the kick-off meeting.
Participants prepare and hold a presentation – either alone or in a group (depending on the number of participants). In their presentation, participants explain, compare and evaluate methods relevant for their specific problem. All presentations should contain a practical example based either on an own dataset or on published research. Participants also take an exam at the end of the course.
Coordination/Contact
Prof. Dr. Karen Gedenk (karen.gedenk@uni-hamburg.de).
For all organiziational issues please contact Elke Thoma (elke.thoma@uni-hamburg.de).