Date: Thu, 9 Feb 2012 13:19:38 -0500
Reply-To: "Mccoach, D. Betsy" <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: "Mccoach, D. Betsy" <firstname.lastname@example.org>
Subject: DATIC Summer workshops in HLM, SEM, Dyadic Analysis, Missing Data
DATA ANALYSIS TRAINING INSTITUTE OF CONNECTICUT (DATIC) is offering five week-long workshops in June and July, 2012. Registration is now open, and you can register online at http://www.datic.uconn.edu/ Space is limited to 24 participants per workshop, so be sure to register early!
Modern Approaches to Missing Data June 4-8, 2012
Instructor: Ofer Harel and Gregory Matthews
Missing data is a common complication in applied research, however, many practitioners are still ignoring this problem. Numerous examples from missing data literature demonstrate that dealing with missing data correctly is very important. Failure to correctly account for missing data creates many potential problems, including biased results, reduced power and inefficient estimates. Multiple Imputation (MI) is a comprehensive method used to handle problems of analyzing incomplete data. This workshop will introduce the vocabulary and main assumptions in the missing data literature followed by the introduction of the main ideas of MI with an emphasis on practical implementation of both fully and semi-parametric procedures. R, an open source (free) statistical software, which has steadily gained in popularity, will be introduced and used as the main statistical software for implementing imputation.
Dyadic Analysis Using Multilevel Modeling June 11-15, 2012
Instructors: David A. Kenny, Tessa V. West, & 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 non-independence, 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.
Hierarchical Linear Modeling (HLM) June 18-22, 2012
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
Dyadic Analysis Using SEM June 25-29, 2012
Instructors: David A. Kenny, Randi Garcia, & 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 non-independence, the actor-partner interdependence and common fate models, mediation and moderation of dyadic effects, and growth curve models of dyadic data. Most of the focus is on distinguishable dyads (e.g., husbands and wives). The software package used in the workshop will be Amos, and it is presumed that participants have some familiarity with Structural Equation Modeling (e.g., model specification, chi square difference, and model fit).
Structural Equation Modeling July 16-20, 2012
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.
DATIC, founded in 2003 by David A. Kenny, offers professional development summer workshops in a variety of modern data analytic techniques. All workshops are geared toward researchers who wish to utilize these techniques in their own work. The maximum enrollment for all DATIC week-long workshops is 24 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. This summer, DATIC will offer 5 week-long training institutes on a variety of data analysis topics. The cost of the workshops is $1100 if registration and payment are received prior to March 1st. Online registration for the workshops is now open.
The cost of registration is $1100 per workshop. Housing is available in the campus hotel or in campus dorms. To register for any of these workshops, please go to http://www.datic.uconn.edu/
D. Betsy McCoach, Ph.D.
Associate Professor, MEA Program
Educational Psychology Department
339 Glenbrook Road, Unit 2064
University of Connecticut
Storrs, CT 06269-2064
Modern Modeling Methods Conference 2011: http://www.modeling.uconn.edu/