Daniel C. Ganster, Colorado State University; and John M. Schaubroeck,
Michigan State University
This seminar will focus on quasi-experimental design, one of the most common methodologies used in internal organizational analytics, as well as in academic research leveraging organizational data or interventions. Specifically, two experts in this area will provide instruction in the real-world design, application, and analysis considerations for conducting organizational research, followed by interactive feedback about participants’ current or upcoming quasi-experimental designs.
Quasi-experiments are evaluations of interventions in which participants cannot be assigned randomly to conditions. Such designs enable organizations to make inferences about the benefits of a new or existing practice or other change to the working environment and/or the environment in which stakeholders (e.g., customers) interface with the organization. This workshop will introduce participants to basic principles of quasi-experimental (QE) design in a way that will enable them to determine when it is appropriate to use a QE design, select appropriate QE designs and analysis strategies, and design a quasi-experiment that optimizes the potential of the study to answer a question(s) of interest to an organization (e.g., Does training first-line supervisors on X improve their Y? If it does, are the increases in Y sustainable over an extended period of time?) with a high level of confidence and at minimal cost. Participants will develop their own QE designs and receive constructive feedback about them. Participants will also be introduced to practical problems encountered in implementing QE designs (e.g., respondent attrition) and learn ways to address these problems.
- Explain the basic elements, advantages, and drawbacks of quasi-experimental (QE) design
- Identify contexts in which QE designs are best suited and select appropriate units of analysis
- Discuss ways in which organizations benefit from QE evaluation designs
- Compare and contrast QE design and analysis approaches, to include methods to mitigate common design pitfalls.
- Design your own quasi-experiment
Daniel C. Ganster is the Partnership for Excellence Professor and Chair of the Management Department at Colorado State University. He received his PhD from Purdue University. His research interests primarily concern work stress and its impact on employee well-being and evaluating organizational interventions aimed at improving work life. He is on the editorial boards of Journal of Applied Psychology, Academy of Management Journal, Journal of Management, Organizational Behavior and Human Decision Processes, and Journal of Occupational Health Psychology.
John M. Schaubroeck is the John A. Hannah Distinguished Professor of Psychology and Management at Michigan State University. He received his PhD. in Organizational Behavior and Human Resource Management from Purdue University. His research interests are related primarily to psychological issues associated with leadership, work related stress and employee health. He has designed and conducted quasi-experiments for organizations in areas such as improving employee well being by introducing new work practices, enhancing leaders’ communication of information related to organizational change, and improving the quality of customer service delivery. He is outgoing editor-in-chief of the Organizational Behavior and Human Decision Processes.
Coordinator: Liuqin Yang, Portland State University.