Training and Professional Development

  • DATIC Workshops 2017 in Quant Methods/Modeling

    The following three workshops still have seats available.  Please visit www.datic.uconn.edu to register.

     

    Structural Equation Modeling using Mplus

    Instructor: D. Betsy McCoach                                                                   June 5th-9th, 2017                                                                     

    This introductory workshop on Structural Equation Modeling covers basics of path analysis, confirmatory factor analysis, and latent variable modeling. Using Mplus, participants will learn how to build, evaluate, and revise structural equation models. Although the workshop does not require any prior knowledge or experience with SEM, participants are expected to have a working knowledge of multiple regression, as well as some experience using a statistical software program such as SPSS.

     

    Longitudinal Modeling using MPlus

    Instructor: D. Betsy McCoach                                                                    June 15th-17th, 2017

    During this a three-day workshop, students will learn how to model longitudinal data using Mplus. The workshop focuses on fitting and interpreting autoregressive and growth curve models in Mplus. Specifically, we will cover linear, polynomial, multiphase, non-linear growth curve models, multivariate growth curve models, autoregressive models, and hybrid autoregressive/growth models for both observed variables and latent constructs. Some prior knowledge and experience in Structural Equation Modeling is recommended.

     

    Multilevel Modeling Using HLM

    Instructor: D. Betsy McCoach                                                                         July 17-21, 2017

    This workshop covers basics and applications of multilevel modeling with extensions to more complex designs. Participants will learn how to analyze both organizational and longitudinal (growth curve) data using multilevel modeling and to interpret the results from their analyses. Although the workshop does not require any prior knowledge or experience with multilevel modeling, participants are expected to have a working knowledge of multiple regression as well as some experience using statistical software (such as SPSS, SAS, R, Stata). All analyses will be demonstrated using the software HLMv7. Instruction will consist of lectures, computer demonstrations of data analyses, and hands-on opportunities to analyze practice data sets using HLM. The workshop emphasizes practical applications and places minimal emphasis on statistical theory.  The workshop takes place in a computer lab, so you do not need to bring a laptop or software. The workshop is limited to 24 participants.

     

    For more information, visit our website: www.datic.uconn.edu

    For more information, contact: Betsy at betsy@uconn.edu