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Final Announcement: CARMA Summer Short Courses- Research Methods for Management and Organization Studies

  • 1.  Final Announcement: CARMA Summer Short Courses- Research Methods for Management and Organization Studies

    Posted 04-22-2008 13:26

    Dear Colleagues (with apologies for cross-postings):

    Please allow me to share this final announcement about upcoming Summer Short Courses on management research methods topics being hosted in May of 2008 by the Center for the Advancement of Research Methods and Analysis (CARMA) at Virginia Commonwealth University in Richmond, Virginia.  Let me also invite you to share this email with colleagues or students who you think might be interested.  As you will see below, the topics of these twelve Short Courses include nonlinear dynamic models (neural network and agent- based models), introductory and advanced structural equation methods, grounded theory methods, repeated measures/longitudinal methods, meta-analysis, multi-level methods, social network analysis, testing interactions with linear regression, survey design/data collection using the internet, introduction to linear regression, and alternatives to difference scores: polynomial regression and response surface methodology.

    Since three of these courses are new, I am also including instructor bios and course descriptions for these courses:

    1.  Nonlinear dynamic models (neural network and agent- based models)
    2.  Introduction to linear regression
    3.  Alternatives to difference scores: polynomial regression and response surface methodology.

    CARMA is an interdisciplinary center with a management/organizational emphasis that is now celebrating its tenth year of operation.  Last summer, over 120 faculty and doctoral students from universities throughout the United States and abroad participated in one or more of our short course events.  CARMA also currently has 120 universities from throughout the world participating in our CARMA Consortium Webcast Program, which has hosted 36 lectures on research topics that have been delivered live and via recordings over the internet. More information about CARMA and the events below can be found at our website:
    (http://www.pubinfo.vcu.edu/carma/).

    Each of the short courses includes an equal balance of lecture and lab time with hands-on experience, with an emphasis on the application of the methodology.  We have a very talented set of instructors for our Short Courses, many of whom are Editors, Past Editors, or Editorial Board members from our leading management journals. They will help you not only learn the technical details of the research method or analysis technique you will be studying, but they will also help you understand how it is being applied in management and organizational research. You can find information about our Short Courses and a summary of evaluations from last year's program on the CARMA website:
    (http://www.pubinfo.vcu.edu/carma/SummerShortCourses.asp).

    The cost per course is $500 for students or $700 for faculty or professionals, and this cost includes lunches, a dinner, and all program materials.  There is also a 50% discount for faculty and students coming from schools participating in our Consortium Webcast Program (a list of participating schools is available on our website: (http://www.pubinfo.vcu.edu/carma/CurrentConsortiumMembers.asp).

    We are very excited that we will be hosting our Summer Short Courses in Snead Hall, our new School of Business Building that we have just moved into, and pictures are available on the School of Business website: (http://www.bus.vcu.edu/).  I am also very happy to report that our main 2008 CARMA Summer Short Course hotel will be the newly remodeled Double Tree Hotel, which is only one block from Snead Hall.  Reservation information is now available:  (http://doubletree.hilton.com/en/dt/groups/personalized/RICFSDT-VMC-20080508/index.jhtml).  We also have other reasonably priced hotel accommodations available.  Snead Hall and the hotels are only 15 minutes from the Richmond Airport, which now provides direct connections to 24 major destination markets via over 200 daily flights.

    Let me encourage you to register early, as some of our courses are full and others are filling up quickly. The full schedule of Short Courses is at the end of this email.

    Nonlinear Dynamic Models: Neural Networks and Agency Based Models
    Dr. Paul Hanges
    University of Maryland
    May 12-14, 2008

    Biography

    Paul J. Hanges is Professor of Industrial/Organizational Psychology and is currently the Associate Chair/Director of Graduate Studies for the University of Maryland's (UMD) Psychology Department. He is also an affiliate of the UMD's R. H. Smith School of Business and the Aston Business School (Birmingham, England). He received his Ph.D. from the University of Akron in 1987. His research focuses on testing and strategic human resource management, diversity and organizational climate, cross-cultural leadership, and mathematical/computational modeling. He has published over 60 articles and book chapters as well as one book. Paul's publications have appeared in such journals as Advances in Global Leadership, American Psychologist, Applied Psychological Measurement, Applied Psychology: An International Review, Journal of Applied Psychology, Journal of International Business Studies, Psychological Bulletin, and The Leadership Quarterly. He is on the editorial board of the Journal of Applied Psychology and The Leadership Quarterly and a fellow of the American Psychological Association, Association for Psychological Sciences, and the Society for Industrial/Organizational Psychology


    Course Summary

    The Nonlinear Dynamic Models Short Course is designed to expose researchers to two common analysis techniques used to develop and test dynamic models.  Specifically, the following topics will be covered:  (a) Introduction to dynamic models and an explanation for why they are needed in the Organizational Sciences, (b) Explanation of neural network analysis, (c) Discussion and interpretation of neural network analysis using SPSS 16, (d) Introduction to agent-based models and explanation of their utility in developing dynamic hypotheses, (e) Downloading and installing shareware agent-based model software, (g) Explanation of software and instruction on programming software, (h) comparison of these two techniques.  This Short Course combines lecture with hands-on experience with these two techniques.  

    Course Outline & Objectives

    Day 1
    1. What are dynamic models and why are they useful?
    2. Explanation of neural network models and illustration of how to test and interpret models using SPSS
    3. Practice performing and interpreting neural network analyses.
    Day 2
    1. What are agent-based models and why are they useful?
    2. Netlogo shareware software illustration of the utility of agent-based models
    3. Practice programming and interpreting agent-based models.
    4. Comparison of the two techniques
    Day 3
     
            1. Illustrative Example: Dynamic Models and Leadership
            2. Other Kinds of Dynamic Models
                           a) catastrophe theory
                           b) genetic algorithms
            3. Wrap up

    Alternatives to Difference Scores:
    Polynomial Regression & Response Surface Methodology
    Dr. Jeff Edwards
    University of North Carolina
    May 15-17, 2008


    Biography

    Jeffrey R. Edwards is the Belk Distinguished Professor of Management at the Kenan-Flagler Business School at the University of North Carolina at Chapel Hill.  He was previously Professor of Organizational Behavior and Human Resource Management at the University of Michigan Business School and Associate Professor of Business Administration at the Darden Graduate School of Business at the University of Virginia.  He holds a B.A. in psychology and economics from the University of North Carolina at Chapel Hill and a M.S. and Ph.D. in organizational psychology and theory from the Graduate School of Industrial Administration from Carnegie Mellon University. He is past editor of Organizational Behavior and Human Decision Processes, has served as associate editor for Organizational Behavior and Human Decision Processes, Organizational Research Methods, the Journal of Organizational Behavior, and Management Science, and has served on the editorial boards of the Academy of Management Journal, the Journal of Applied Psychology, Personnel Psychology, Organizational Research Methods, the Journal of Organizational Behavior, the Journal of Management, the Journal of Occupational Health Psychology, and Social Indicators Research.  He is a Fellow of the Academy of Management, the American Psychological Association, the Society of Industrial and Organizational Psychology, and the Center for the Advancement of Research Methods and Analysis (CARMA) and has been elected to the Society of Organizational Behavior.  He has also been elected to various positions within the Academy of Management, including representative at large of the Organizational Behavior Division and representative at large, program chair, and division chair of the Research Methods Division.  He is also founder and coordinator of RMNET, the electronic question-and-answer discussion group for members of the Research Methods Division.
     
    Professor Edwards' research and teaching focus on person-environment fit in organizations, stress, coping, and well-being, the work-nonwork interface, and methodological issues in organizational research. His methodological work has examined difference scores, polynomial regression, and measurement and construct validation using structural equation modeling. His work has been published in the Academy of Management Review, the Academy of Management Journal, the Journal of Applied Psychology, Personnel Psychology, Organizational Behavior and Human Decision Processes, Human Relations, the Journal of Organizational Behavior, Psychological Methods, and Organizational Research Methods.  He has taught courses in undergraduate, MBA, doctoral, and executive education programs on topics such as organizational behavior, individual and organizational change, stress management, employee involvement, human resource management, and research methods. His research methods course has won awards at the school and university levels.  He has served as an instructor and consultant for Alcoa, Burlington Industries, ExxonMobil, General Electric, General Motors, GlaxoSmithKline, Johnson & Johnson, Kaiser Permanente, Misys Healthcare, Quintiles, SonyEriccson, Wachovia, W.C. Bradley, Westinghouse, Whirlpool, and the U.S. Department of Defense.

    Course Summary

    For decades, difference scores have been used in studies of fit, similarity, and agreement in organizational research.  Despite their widespread use, difference scores have numerous methodological problems. These problems can be overcome by using polynomial regression and response surface methodology to test hypotheses that motivate the use of difference scores.  These methods avoid problems with difference scores, capture the effects difference scores are intended to represent, and can examine relationships that are more complex than those implied by difference scores.  

    This short course will review problems with difference scores, introduce polynomial regression and response surface methodology, and illustrate the application of these methods using empirical examples.  Specific topics to be addressed include: (a) types of difference scores; (b) questions that difference scores are intended to address; (c) problems with difference scores; (d) polynomial regression as an alternative to difference scores; (e) testing constraints imposed by difference scores; (f) analyzing quadratic regression equations using response surface methodology; (g) difference scores as dependent variables; and (h) answers to frequently asked questions.


    Linear Regression Models
    Dr. Jose Cortina
    George Mason University
    May 12-14, 2008

    Biography

    Jose M. Cortina is a Professor in the I/O Psychology program at George Mason University.  Professor Cortina received his Ph.D. in 1994 from Michigan State University.  His recent research has involved topics in meta-analysis, structural equation modeling, and the use of personality to predict job performance.  His work has been published in journals such as the Journal of Applied Psychology, Personnel Psychology, Psychological Bulletin, Organizational Research Methods, and Psychological Methods.  He currently serves on the editorial boards of four journals and is an Associate Editor of the Journal of Applied Psychology.  Dr. Cortina was honored by SIOP with the 2001 Ernest J. McCormick Award for Distinguished Early Career Contributions and by the Research Methods Division of the Academy of Management with the 2004 Robert O. McDonald Best Paper Award.

    Course Summary

    The general purpose of this course, besides torture which, sadly, has been prohibited by APA, is to subject you to all, or at least much, that is regression analysis (How's that for a sentence?).  Specifically, we will cover the nuts and bolts of standard linear regression (i.e., excluding things like logistic regression and random coefficient modeling).  This will allow you to address a wide variety of research questions, to identify those questions which are not appropriately addressed with standard regression analysis, and to isolate the problems associated with any given regression analysis.

    Only so much material can be covered in 3 days.  If you expect to be a regression expert in that time, you will be disappointed.  On the other hand, if you need a foundation on which to build expertise, then you have come to the right place.  At the end of this course, you will have a basic understanding of the questions to which regression applies, of the interpretation of regression output, and of the most important assumptions on which OLS regression is based.
     
    Course Outline & Objectives

    I. Review of simple regression (Chs 1 and 2)
    A. Purpose of regression
    B. Line of best fit
    1. Errors and least squares criterion
    2. Calculation of b and a
    C. Standard error of estimate
    D. Meaning of b
    E. Standardized approach
    II. Assumptions of regression (Berry & Ch.4 of Cohen)
    A.        Y is continuous
    B.        Predictors are interval level
    C.        No measurement error
    D.        Model is intrinsically linear and additive
    IV. General multiple regression (Chs. 3 & 5)
    A. Meaning of b
    B. Meaning of R
    C. Shrinkage
    D. Multicollinearity
    E. Entry of predictors
    V. Regression with dummies (Chs. 8 & 9)
    A. How does one cope with categorical predictor variables in regression?
    B. How are the results interpreted?
    VI. Advanced topics

    Complete Schedule for 2008 CARMA Summer Short Courses

    May 12-14 (Mon-Wed noon)

    Nonlinear Dynamic Models:  Neural Networks and Agency Based Models
    Dr. Paul Hanges, University of Maryland
                           
    Introduction to Structural Equation Methods                        
    Dr. Larry J. Williams, Virginia Commonwealth University        
                                                           
    Repeated Measures/Longitudinal Research
    Dr. Robert Ployhart, University of South Carolina
                   
    Meta Analysis: Models and Processes                        
    Dr. Mike McDaniel, Virginia Commonwealth University        
    Dr. Hannah Rothstein, Baruch College                        
                                                           
    Multi-Level Analysis Methods                                
    Dr. Paul Bliese, Walter Reed Army Institute of Research        
           
    Introduction to Linear Regression
    Dr. Jose Cortina, George Mason University

    May 15-17 (Thurs-Sat noon)

    Advanced Topics in Structural Equation Methods
    Dr. Robert Vandenberg, University of Georgia
                           
    Social Network Analysis
    Dr. Stephen Borgatti, Boston College

    Testing Interactions with Linear Regression
    Dr. Herman Aguinis, University of Colorado Denver

    Survey Design/ Data Collection Using the Internet
    Dr. Jeff Stanton, Syracuse University

    Alternatives to Difference Scores: Polynomial Regression and Response Surface Methodology
    Dr. Jeff Edwards, University of North Carolina
                                                           
    Grounded Theory Method and Analysis
    Dr. Karen Locke, College of William and Mary                                                
                                           
    We hope you will find our Short Course offerings to be of interest and we would be very happy to have you participate in our instructional program. Please let us know if you have any questions or if we can help in any way.  Hope to see you in May!


    Sincerely,

    Dr. Larry J. Williams
    University Professor of Management
    Virginia Commonwealth University
    CARMA Director



    Dr. Larry J. Williams, Director
    Center for the Advancement of Research Methods and Analysis (CARMA)
    http://www.pubinfo.vcu.edu/carma/
    Virginia Commonwealth University
    301 W. Main Street, Snead Hall
    PO Box 844000
    Richmond, VA 23284-4000
    phone: 804-828-7163
    fax: 804-225-4790