Data Analysis Training Institute of Connecticut 2015 Summer workshops: www.datic.uconn.edu
DATIC (datic.uconn.edu ) offers professional development summer workshops in a variety of modern data analytic techniques. All workshops are applied and are geared toward researchers who wish to utilize these techniques in their own work. The maximum enrollment for all DATIC week-long workshops is 25 students, which allows for personal contact with the instructors and a great deal of hands-on learning. Although all workshops are introductory, they do assume familiarity with traditional statistical techniques such as multiple regression, as well as familiarity with a general purpose statistical software package, such as SPSS, SAS, R, Stata, etc. DATIC is pleased to announce the following course offerings for 2015:
Structural Equation Modeling
June 8-12, 2015
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.
Dyadic Data Analysis Using Multilevel Modeling
June 15-19, 2015
Instructors: David A. Kenny and Tessa V. West
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.
Meta-Analysis
June 17-19, 2015
Instructor: Noel Card
This course teaches the skills necessary to conduct and write publishable meta-analytic reviews, including methods of searching the empirical literature, coding effect sizes, and analyzing effect sizes across multiple studies. Specifically, this course will enable participants to: (1) Understand and critically evaluate published meta-analyses; (2) Develop the skills necessary to conduct and write publishable meta-analytic reviews; and (3) Identify the foundations upon which more advanced meta-analytic techniques are based.
Hierarchical Linear Modeling (HLM)
June 22-26, 2015
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.
For more information or to register, please go to datic.uconn.edu
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