Data Analysis Training Institute of Connecticut (DATIC) will be offering three one- week workshops on Dyadic Analysis, Structural Equation Modeling, and Hierarchical Linear Modeling in June 2013 at the University of Connecticut. Brief
descriptions of the 3 workshops are below. Online registration is currently open, and space is limited to 24 participants per workshop, so please register early. For more information or to register for the workshops, go to http://www.datic.uconn.edu
Dyadic Data Analysis Using Multilevel Modeling
June 3-7, 2013
Instructors: David A. Kenny and Randi Garcia The workshop on dyadic data analysis will focus on data where both members of a dyad are measured on the same set of variables. Among the topics to be covered are the measurement of nonindependence,
the actor-partner interdependence model, the analysis of distinguishable and indistinguishable dyads, mediation and moderation of dyadic effects, and over-time analyses of dyadic data. The software package used in the workshop will be SPSS, but there will
be discussion of other packages (e.g., HLM) and structural equation modeling. 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 or
analysis of variance, as well as SPSS.
Structural Equation Modeling
June 10-14, 2013
Instructor: D. Betsy McCoach
This introductory workshop on Structural Equation Modeling covers basics of path analysis, confirmatory factor analysis, and latent variable modeling. Using AMOS Graphics, 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.
Hierarchical Linear Modeling (HLM)
June 17-21, 2013
Instructors: D. Betsy McCoach, & Ann A. O'Connell
Each HLM 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 SPSS (or SAS). Analyses
will be demonstrated using the software HLMv7. Instruction will consist of lectures, computer workshops, and individualized consultations. The workshop emphasizes practical applications and places minimal emphasis on statistical theory.
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