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Methods: Mind the Gap

Webinar Series

Time-Varying Effect Modeling To Study Developmental and Dynamic Processes

January 29, 2016
Stephanie T. Lanza, Ph.D.
​Stephanie Lanza, Ph.D.

Professor, Department of Biobehavioral Health
College of Health and Human Development, The Methodology Center
The Pennsylvania State University

View the Webinar

About the Webinar

Time-varying effect modeling (TVEM) is a novel method that enables health, behavioral, and social scientists to examine developmental (i.e., age-varying) and dynamic (i.e., time-varying) associations. TVEM estimates regression coefficients as non-parametric functions of continuous age or time.

This method can be applied to existing cross-sectional or longitudinal data to answer novel questions such as: How does the association between a particular contextual risk factor and health behavior vary across age? How do these complex associations differ across population subgroups?

TVEM also can be applied to intensive longitudinal data such as ecological momentary assessments to reveal dynamic processes, addressing questions such as: How does the association between mood and craving unfold with time during a smoking quit attempt?

The goal of this talk is to produce new research questions that can be addressed using TVEM, and to provide resources for researchers interested in using the models in their own work.

About Stephanie Lanza

Stephanie Lanza is a Professor of Biobehavioral Health and Scientific Director of The Methodology Center at Penn State. She has a background in research methods, human development, and substance use and comorbid behaviors, with papers appearing in both methodological and applied journals.

She is co-author of the book Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences (published by Wiley in 2010) and led the development of PROC LCA, a Science Analysis System (SAS) procedure for fitting latent class models.

Her research interests include advances in finite mixture modeling and time-varying effect modeling to address innovative research questions in public health science. She is passionate about disseminating these methods to health, behavioral, and social science researchers, and has organized many NIH-funded dissemination conferences, taught many hands-on workshops, and written tutorial articles to enable applied researchers to use the latest methods in their own work.

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