Topic: An Introduction to Time-Varying Effect Modeling
Date: June 11-12, 2015
Venue: Bethesda North Marriott Hotel & Conference Center, North Bethesda, MD
The goal of this two-day workshop is to help you gain the theoretical background and applied skills to be able to identify and address interesting, new research questions using time-varying effect modeling (TVEM). Application of these models to examine time-varying effects using intensive longitudinal data such as ecological momentary assessments, as well as age-varying effects using cross-sectional and panel data, will be introduced. By the end of the workshop, participants will have fit several time-varying effect models in SAS and will have had the opportunity to fit preliminary models to their own data.
Workshop time will be spent in lecture, software demonstrations, computer exercises, and discussion. At the workshop, participants will be provided with a hard copy of all lecture notes, select computer exercises and output, and suggested reading lists for future reference. The software used in this course is a suite of SAS macros, downloadable software that is developed at the Penn State Methodology Center. Part of the second afternoon will be reserved for participants to apply the concepts learned in class to their own data, and the presenters will be available for consultation during that period.
The prerequisite for this workshop is graduate-level statistics training for the behavioral or health sciences up through linear regression (usually two semesters of course work). Basic familiarity with SAS and logistic regression is helpful, but not a prerequisite.
Participants are strongly encouraged to bring a laptop so that they can conduct the computer exercises and analyze their own data. To conduct analyses at the workshop, SAS Version 9 for Windows must be installed on the laptop prior to arrival. In addition, approximately one week prior to the workshop participants will be sent an email requesting that they download the TVEM SAS macro suite. Participants must verify that data use agreements permit them to bring their own data to the workshop. Simulated data will be made available to those who do not bring their own data.
Topics to be covered:
- Conceptual introduction to time-varying effect modeling (TVEM)
- Regression, logistic regression, and multilevel modeling – a review
- Multilevel modeling versus TVEM
- TVEM for modeling time-varying effects in intensive longitudinal data
- Model interpretation, model selection
- TVEM for modeling age-varying effects in cross-sectional and panel data
In addition to the above topics, there will be several hands-on computer exercises, open discussion times, and question/answer periods.
How to attend
Enrollment is limited to 40 participants to maintain an informal atmosphere and to encourage interaction between the presenters and participants, as well as among participants. We give priority to individuals who are involved in drug abuse prevention and treatment research or HIV research, who have appropriate statistical background to get the most out of the Institute, and for whom the topic will have a direct and immediate relevance to their current work. We also aim to maximize geographic and minority representation.
To attend the 2015 Summer Institute, submit an application. Applications are due by Friday, March 6, 2015 at 5 p.m. EST. Applicants will be notified about decisions by Tuesday, March 31, 2015.
Once accepted, participants will be emailed instructions about how to register. The registration fee of $395 for the two-day Institute covers all instruction, program materials, refreshment breaks, and lunch each day. Participants are encouraged to bring their own laptop computers for conducting exercises.
Review our refund, access and cancellation policies.
Who are the presenters?
Stephanie Lanza, Ph.D.
Scientific Director and Senior Research Associate, The Methodology Center
Research Associate Professor, College of Health and Human Development
I work primarily in two methodological areas. Much of my work seeks to advance finite mixture models, particularly latent class analysis. My primary collaborators on this project include Bethany Bray, Brittany Rhoades Cooper, and John Dziak. I also work to advance and apply new statistical models in order to reveal dynamic processes. Much of this work, done in collaboration with Runze Li, Sara Vasilenko, and Megan Piper, addresses new research questions using intensive longitudinal data related to drug abuse.
Sara Vasilenko, Ph.D.
Research Associate, The Methodology Center
My primary interest is applying innovative methods to study adolescent and young adult development, health, and well-being, with a focus on the development of sexual behavior. I am collaborating with Stephanie Lanza and Runze Li on applications of TVEM to research on sexual behavior and substance use. I am also using LCA to examine multidimensional patterns of sexual and romantic behaviors with Stephanie Lanza and Kari Kugler.
Where is it being held?
5701 Marinelli Road
North Bethesda, MD 20852
A block of rooms will be available at the hotel. Reservations must be received on or before Wednesday, May 20, 2015 (the "cut-off date"). To make reservations under the Summer Institute contract, please call 1-800-228-9290 or 1-301-822-9200.
- 2014 - Experimental Design and Analysis Methods for Developing Adaptive Interventions: Getting SMART by Daniel Almirall, Ph.D. and Inbal Nahum-Shani, Ph.D.
- 2013 - Introduction to Latent Class Analysis by Stephanie T. Lanza, Ph.D. and Bethany C. Bray, Ph.D.
- 2012 - Causal Inference by Donna L. Coffman, Ph.D.
- 2011 - The Multiphase Optimization Strategy (MOST) by Linda Collins, Ph.D.
- 2010 - Analysis of Longitudinal Dyadic Data by Niall Bolger, Ph.D. and Jean-Philippe Laurenceau, Ph.D.
- 2009 - Latent Class and Latent Transition Analysis by Linda M. Collins, Ph.D. and Stephanie T. Lanza, Ph.D.
- 2008 - Statistical Mediation Analysis by David P. MacKinnon, Ph.D.
- 2007 - Mixed Models & Practical Tools for Causal Inference by Donald Hedeker & Joe Schafer
- 2006 - Causal Inference by Chris Winship & Felix Elwert
- 2005 - Survival Analysis by Paul D. Allison
- 2004 - Analyzing Developmental Trajectories by Daniel S. Nagin
- 2003 - Modeling Change and Event Occurrence by Judith D. Singer & John B. Willett
- 2002 - Missing Data by Joseph Schafer
- 2001 - Longitudinal Modeling with MPlus by Bengt Muthén & Linda Muthén
- 2000 - Integrating Design and Analysis & Mixed-Effect Models by Richard Campbell, Paras Mehta & Donald Hedeker
- 1999 - Structural Equation Modeling by John J. McArdle
- 1998 - Categorical Data Analysis by David Rindskopf & Linda Collins
- 1997 - Hierarchical Linear Models and Missing Data Analysis by Stephen Raudenbush & Joseph Schafer
- 1996 - Analysis of Stage Sequential Development by Linda Collins, Peter C.M. Molenaar & an L.J. van der Maas