Using Meta-Analysis to Inform the Robustness of Research Findings
Associate Professor/Dean’s Council of 100 Distinguished Scholar
Department of Management and Entrepreneurship
W. P. Carey School of Business
Arizona State University
Tempe, AZ 85287
Zhen Zhang is associate professor of management and Dean’s Council of 100 Distinguished Scholar in the Department of Management and Entrepreneurship at the W. P. Carey School of Business, Arizona State University. His research focuses on leadership process and leadership development, work teams and groups, biological basis of work behavior, start-ups and entrepreneurship, and advanced research methods. Zhang’s work has appeared in leading management journals including Academy of Management Journal, Personnel Psychology, Journal of Applied Psychology, Organization Science, Organizational Behavior and Human Decision Processes, and the Leadership Quarterly, and has been cited in media outlets such as the Wall Street Journal, New York Times, and the Globe and Mail. He currently serves as an associate editor of Personnel Psychology. Zhang has taught graduate and undergraduate courses of Organizational Behavior, Leadership, and Cross-Cultural Management.
This presentation focuses on examining and interpreting effect size heterogeneity in meta-analysis findings, and methods of incorporating heterogeneity in the two approaches of combining meta-analysis and structural equation modeling. We first review the various measures of effect sizes in organization sciences and how meta-analyses report information about effect size heterogeneity. We then compare and contrast two approaches that test structural models based on meta-analytically derived correlations. Based on recent research (Cheung, in press; Yu et al., 2016), we show how heterogeneity can be considered in these two approaches. Recommendations are provided for researchers to better use the rich information of effect size heterogeneity when they evaluate primary studies and/or conducting meta-analyses.
Digital Reader: Resources Recommended by the Speaker
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