Research Methods Workshops (SWARM)
Successfully run over the last several summers and attracting participants from the US, Europe and the Far East, Coller's Summer Workshops in Advanced Research Methods (SWARM) are 3 to 4-day state-of-the-art methodological workshops designed for junior faculty and PhD students in business and management and related fields (the social and medical sciences). Each workshop consists of 30 contact hours, with transfer credit available.
SWARM provides its participants with a hands-on setting for following the latest advances in statistical analysis, keeping up to date with available applications and improving their technique. Taught by scholars at the forefront of methodology design from the Coller School of Management, SWARM workshops are offered in several key sets of advanced research methods: advanced regression, structural equation modeling and multi-level modeling.
SWARM 2018 Academic Director - Prof. Avi Carmeli, Coller School of Management
SWARM 2018 will be held in June, 2018. It will consist of three separate workshops, each focusing on a specific type of statistical modeling.
1st - Advanced Regression Analysis by Prof Ayala Cohen & Dr. Dana Vashdi : 14,15, and 17 June 2018
Topics: Moderation, Mediation, Moderated Mediation, Logistic Regression ( Binary Dependent Variable), Poisson Regression , ( Count Dependent Variable)
2nd - Mplus by Prof. Mo Wang: 20, 21, and 22 June 2018
Mo Wang, Ph.D. ,Lanzilotti-McKethan Eminent Scholar Chair Editor, Work, Aging and Retirement, Associate Editor, Journal of Applied Psychology
3rd - Multilevel Research Analysis by Prof. Gilad Chen: 24, 25, and 26 June 2018
Lecture: Gilad Chen, Ph.D., Robert H. Smith School of Business, University of Maryland; Editor-in-Chief, Journal of Applied Psychology
Topics: Random Coefficient Models – HLM, rWG, ICC; Cross-level Effects, Cross-level Moderation; Growth Models
- Ph.D. students in any area of business administration (e.g., Organizational Studies, Strategy, Management, Marketing and Consumer Behavior) with some background in multivariate statistical analysis
- Junior Faculty in schools of business administration, or any social science discipline
- Ph.D. students in any of the Social Sciences (e.g., psychology, sociology, social work, economics, political science)
- Physicians and other medical sciences researchers