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AOM PDW (session# 466) : How To Make Up Data: An Introduction to Computer Simulation

  • 1.  AOM PDW (session# 466) : How To Make Up Data: An Introduction to Computer Simulation

    Posted 19 days ago
    Edited by Alex Rubenstein 15 days ago

    Have you ever wanted to create simulated data, whether for research purposes or for teaching? And do you feel that you don't even know where to start, as it seems that it may require a lot of math and computer programming that were not part of your training? If so, then please join us for the PDW session:

    "How to Make Up Data: An Introduction to Computer Simulation"  
    Session# 466 | Sponsors: HR, OB, RM, STR
    Session Format: In-person Only: Seattle
    Schedule: Saturday August 6, 1:30-3:30PM (Pacific Time)
    at The Seattle Convention Center, Room 612.

    Coordinator: Michael C. Sturman, Rutgers U., School of Management and Labor Relations
    Facilitator: Hanbo Shim, U. of Texas at Arlington
    Facilitator: Sanghee Park - Hanyang U. 
    Facilitator: Xueqing (Skye) Fan - Rutgers U., School of Management and Labor Relations

    This PDW is designed for those with little or no experience with using computers to generate simulated data. The PDW will begin with the very simple case of generating two correlated variables, but ultimately describe how to create multivariate data with desired relationships, dichotomous and categorical variables, with observed multi-item measures with a desired level of reliability, and with moderated and non-linear relationships. To help learners of all sorts, instruction will be given on how to conduct simulation in Excel, Mplus, and R, and you can choose which program you want to use for your examples. The PDW combines instruction with hands-on exercises, with the PDW facilitators helping you as needed to complete each of the examples given. No programming knowledge or advanced mathematics are required, although participants should be familiar with at least one of the three example programs and be comfortable with correlations and regression. Participants will receive the files in all three programs for the examples covered during the session. By the end of the sessions, participants should be able to create on their own a given dataset with their desired characteristics. Participants should bring their own computers with their preferred software (Excel, Mplus, or R) so that they can participate in the exercises.

    The session is open to all attendees and does not require pre-registration. If you have any questions, please feel free to contact the PDW coordinator Michael Sturman at michael.sturman@rutgers.edu.

    Hanbo Shim
    Assistant Professor
    University of Texas At Arlington
    Arlington TX