DATA ANALYSIS TRAINING INSTITUTE OF CONNECTICUT
DATIC will offer the following five workshops at the University of Connecticut in June 2014. Registration is now open. Register early! Space is limited!
For more information or to register, go to www.datic.uconn.edu .
R-project for Statistical Computing: June 4, 2014 $150 ($100 Students)
Instructor: Tania B. Huedo-Medina
This one-day workshop will introduce R project for Statistical Computing. We will explain the particularities of R compare to the mainstream commercial packages, and we will present the more than 5,000 free packages that R has to run statistical analysis and create publication quality graphics. At the end of the workshop the participants should be able to manage data, perform basic statistics and graphics, and generalize these skills to use R packages that will allow them to run more advanced statistical analyses.
Meta-Analysis Using R: June 5-6, 2014 $250 ($150 Students)
Instructor: Tania B. Huedo-Medina
Over the past 40 years, research exploring the links between biological, psychosocial, behavioral, and educational factors has grown exponentially. Understanding and reporting these interrelated factors that underlie individual variability will result in the most accurate evidence-based knowledge over time and across a variety of populations and intervention characteristics. To summarize these large masses of evidence, meta-analytic methods have seen sharply increased use across sciences, including many topics ranging from medical to social and behavioral sciences. As a consequence, the statistical techniques to conduct meta-analysis have been extended and improved intensely in the last 10 years to support an efficient and valid practice of meta-analysis. This workshop is a comprehensive introduction to those advanced statistical methods that have been developed recently in meta-analysis. At the end of the two days, you will be able to run meta-analytic methods under different statistical approaches that can capture and test complex models using meta-analysis.
Dyadic Analysis: June 9-13, 2014 $1100
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.
Structural Equation Modeling: June 16-20, 2014 $1100
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: June 23-27, 2014 $1100
Instructors: D. Betsy McCoach and Ann A. O'Connell
Each HLM workshop covers basics and applications of miltilevel 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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