Friday Seminar 4
Conceptual and Methodological Issues in Analyzing Changes Over Time
Robert J. Vandenberg
University of Georgia
Singapore Management University
This seminar will introduce the fundamental issues involved in the analysis of change over time and focus on a specific data analysis procedure referred to as latent growth modeling (LGM) for assessing the various facets of change over time. Examples of the types of applications in which the seminar providers have been involved include (a) how the rate of change in commitment to the organization over time impacts change in turnover intention and actual turnover behavior; (b) examining the formation (i.e., change in) of newcomers’ adjustment to the workplace as a function of the socialization practices to which they are exposed; and (c) assessing intervention effectiveness over time by comparing the change in safety climate between treatment and control work sites. LGM may be applied to most any type of variable where change is a key component (e.g., change in employee attitudes, in employee performance, in organizational financial performance, etc.). Further, it can be used to examine the influence of change in one type of variable on the change in another type of variable (e.g., impact of change in work team cohesiveness over time upon team performance). There are two lines of thought in LGM, one growing out of a random coefficient modeling tradition best represented by Singer and Willet (2003), and another from a structural equation modeling (SEM) tradition best represented by Bollen and Curran (2006). This seminar will follow the SEM tradition. We will start with explicating several fundamental questions about the various facets of change over time and discussing some basic requirements for the study of change across time. Next, we will present a series of actual examples, beginning with the simplest basic model that illustrates the basic elements to an LGM and progressing through examples of increasingly complex models to the final example of a complex model which incorporates multiple focal change variables and multiple predictors and correlates. The examples will be presented using either LISREL or the Mplus statistical analysis packages for latent variables. We will end by discussing how latent growth modeling could provide a powerful framework for answering various substantive and applied research questions that could not be answered using traditional data analytic procedures.
- Describe the fundamental issues involved in the analysis of change over time.
- Explain the basic logic of latent growth modeling.
- Demonstrate basic skills for specifying appropriate latent growth models.
- Apply latent growth models to different research questions involving changes over time.
Robert (Bob) Vandenberg is a professor of management in the Terry College of Business at the University of Georgia, Athens, GA. He belongs to the organizational behavior group. He teaches in the undergraduate, MBA and PhD programs including courses in organizational behavior, leadership, change management, introductory research methods, introduction to structural equation modeling, and advanced structural equation modeling. Bob’s primary substantive research focuses are on organizational commitment, and high-involvement work processes. His methodological research stream includes measurement invariance, latent growth modeling, and multilevel structural equation modeling. Bob’s articles on these topics have appeared in the Journal of Applied Psychology, Journal of Management, Journal of Organizational Behavior, Human Resource Management, Organization Sciences, Group and Organization Management, Organizational Behavior and Human Decision Processes, and Organizational Research Methods. Bob’s measurement invariance article co-authored with Charles Lance received the 2005 Robert McDonald Award for the Best Published Article to Advance Research Methods given by the Research Methods Division of the Academy of Management. He has served on the editorial boards of the Journal of Applied Psychology, Journal of Management, Organizational Behavior and Human Decision Processes, and Organizational Research Methods, and is currently the editor-in-chief of the latter journal. He is past division chair of the Research Methods Division of the Academy of Management. In addition, he is a Fellow of the American Psychological Association, SIOP, and the Southern Management Association.
David Chan received his PhD in I-O psychology from Michigan State University. He is currently professor of psychology and interim dean at the School of Social Sciences, Singapore Management University. His research includes areas in personnel selection, longitudinal modeling, and adaptation to changes at work. He has published numerous journal articles, authored several Handbook chapters in the fields of measurement, data analysis, and organizational psychology, coauthored a textbook in personnel selection, and delivered several invited keynote speeches. He has received several scholarly awards including the Distinguished Early Career Contributions Award, the William Owens Scholarly Achievement Award, and the Edwin Ghiselli Award for Innovative Research Design presented by SIOP and the Dissertation Research Award presented by the American Psychological Association. In 2000, he was ranked 9th in the list of Top 100-most published researchers of the 1990’s in the field of I-O psychology. He serves as senior editor of the Asia Pacific Journal of Management, associate editor of the Journal of Organizational Behavior, a member on the editorial boards of several other journals such as Personnel Psychology, Human Performance, and Organizational Research Methods. He is currently an elected representative-at-large member of the Executive Committee of the Research Methods Division, Academy of Management. He has worked with several public and private organizations in Singapore and United States on personnel selection and related projects. He is a member of the National Council on Problem Gambling and chair of the Council’s Committee on Service Delivery and Research, a member of the National Youth Council’s Advisory Panel on Youth Research, and a member of an advisory panel to the Singapore government on interagency issues in social science research.
Coordinator: Jennifer Kaufman, Dell
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