DATIC Workshop: Hierarchical Linear Modeling

David A. Kenny
December 16, 2009

~ DATIC 2010 ~
Data Analysis Training Institute of Connecticut

Workshop on Hierarchical Linear Models

Instructors:

D. Betsy McCoach, Ph. D.

University of Connecticut

Ann A. O'Connell, Ed.D.
The Ohio State University

Main DATIC Website

Overview

Registration Details

Benefits

Curriculum

Recommended Readings

Overview

Two workshops on Hierarchical Linear Models will be held at the University of Connecticut (both workshops cover the same material). Dates are:
Session A: Monday, June 14 through Friday, June 18
Session B: Monday, June 21 to Friday, June 25

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. While 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 HLMv6.. Instruction will consist of lectures, computer workshops, and individualized consultations. The workshop emphasizes practical applications and places minimal emphasis on statistical theory.

Because the number of spaces is limited, please apply soon to reserve a space. To register, send an email to daticworkshops@gmail.com in order to save a place, and complete the registration form (click here to get the form).

Participants are encouraged to bring their own data. They should contact the instructors beforehand to ensure that data are appropriately formatted for analysis using HLM or SPSS.

The workshop covers the following topics:

Random and fixed effects
Intraclass correlation and estimation of proportion of variance explained
Methods of centering
Two-level general linear models
Three-level general linear models
Applications of two- and three-level models to organizational data
Applications of two- and three-level models to longitudinal data
The flexible treatment of time within multilevel models
Piecewise Growth Curves using HLM
Two-level generalized (logistic) linear models
Multivariate Hierarchical Linear Models (HMLM)

Registration Details

Dates and Times:

HLM Workshop Session A: Monday June 14 to Friday June 18, 2010

Opening Reception planned for Sunday June 13, at 6:00PM

HLM Workshop Session B: Monday June 21 to Friday June 25, 2010

Opening Reception planned for Sunday, June 20, at 6:00PM

Schedule: 9AM to 5PM Monday-Thursday,

9AM to 12PM Friday with complimentary luncheon

Location:

University of Connecticut, Storrs, Connecticut USA
Nearest Airport: Hartford/Springfield (Bradley International Airport)
Getting to the University of Connecticut by Car
Nathan Hale Hotel

Cost:

Workshop $950 (before April 1)
Workshop $1050 (after April 1)

Workshop $950 (for anyone registering after April 1)

For Housing information and Cancellation policy - please see main DATIC website: http://davidakenny.net/datic/datic.htm

Registration:

Link to Regform.doc (please send check made payable to the University of Connecticut)

Benefits

The following materials and events are included in the cost of the workshop:

CD-ROM containing workshop instructional materials and sample data sets
Binder with workshop outline, computer outputs, and reprints
Sunday pre-workshop reception
Continental breakfast each morning
Friday luncheon

Curriculum (to be adapted somewhat to the specific needs of participants)

Day 1
       - Introduction
       - Basics of multilevel modeling
       - Fixed and random effects, ICC
       - Examples of two-level models for clustered data
       - Using the HLMv6 software
       - Intro to HLM Software
       - Applications (HLMv6)

Day 2
       - Model building, model testing,
       - Estimation, model fit
       - Centering
       - Heterogeneous Variances
       - Using SPSS for two-level organizational data
       - Lab time

Day 3
       - Reconceptualizing longitudinal data for multilevel models
       - Two-level longitudinal analyses
       - The flexible treatment of time
       - Adding time invariant predictors
       - Adding time-varying predictors
       - Applications
       - Lab time

Day 4
       - Developing the piecewise growth curve
       - Polynomial models for non-linear growth
       - Three-level longitudinal analyses
       - Generalized multilevel Linear Models (Logistic HLM)
       - Multivariate Hierarchical Linear Models (HMLM)

-   Lab Time

Day 5
       - Power Analysis and effect size; Using the Optimal Design Software
       - Questions and answers
       - Wrap-up
       - LUNCHEON

Recommended Readings (additional readings to be provided at the course)

O'Connell, A.A. & McCoach, D.B. (Eds.) (2008). Multilevel Modeling of Educational Data. Charlotte, NC: Information Age Publishing.

Raudenbush, S.W. & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Newbury Park, CA: Sage.

Raudenbush, S., Bryk, A., Cheong, Y.F., & Congdon, R. (2004). HLM 6: Hierarchical Linear and Nonlinear Modeling. Lincolnwood, IL: Scientific Software International.

Singer, J. D. & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford: Oxford University Press.

Link to the IAP website to buy the O'Connell & McCoach book here.

Link to the SSI site to buy the Raudenbush & Bryk books here.