LEARNING OUTCOMES
This is an advanced-level course that is designed for students that have already some experience in using quantitative research designs and data analysis techniques in their own research. The goal of the course is to develop a more thorough understanding of how and why certain techniques are used and what principles these techniques are based on. Another goal is to gain mastery in Stata or R statistical software.
The course focuses on causal models, longitudinal and multilevel designs, and corresponding analyses. The techniques covered include all advanced econometrics and latent variable techniques used in Academy of Management Journal, Journal of Applied Psychology, Journal of Management, Journal of Operations Management, Journal of Organizational Behavior, The Leadership Quarterly, Organization Science, Personnel Psychology, and Strategic Management Journal in the recent yearss (see https://doi.org/10.1177/1094428119877457) . The focus of the course will be on how these techniques can be used to empirically support causal claims taking particularly the issues of endogeneity and measurement validity into account.
Credits: 6 - 10
Schedule: 08.10.2024 - 15.04.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Mikko Rönkkö
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
This is a blended learning course that contains both asynchronous online and in-person/synchronous online elements. The teaching mode depends on the student preferences.
The course consists of ten units, that each take two to four weeks and contain video lectures, online and in-person/synchronous online discussions, and assignments. The number of credits varies between 6-10 depending on which assignments students choose to complete. The content of each course component is explained later in the course brochure. All data analysis assignments can be completed with Stata or R. Mplus can be used for some of the assignment or their parts.
Assessment Methods and Criteria
valid for whole curriculum period:
Class participation, online participation, written assignments, data analysis assignments, pre-exam anad final exam.
Workload
valid for whole curriculum period:
See syllabus.
DETAILS
Study Material
valid for whole curriculum period:
Video lectures, empirical articles, methodological articles, books about methods. See the course syllabus for details.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - Spring V
2025-2026 No teaching