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2012 Summer Institute: Causal Inference
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Donna Coffman, Ph.D. |
We are pleased to announce that Methodology Center Principal Investigator Donna Coffman will present this year's Summer Institute on Innovative Methods, "Propensity Score Methods for Causal Inference."
Sponsored by The Methodology Center and the National Institute on Drug Abuse, the 17th Summer Institute will describe statistical, methodological, and conceptual aspects of propensity score methods for causal inference. The Institute will be held on June 21-22, 2012 at the Penn Stater Conference Center and Hotel in State College, PA. Please spread the word.
Read more or register. |
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Featured Article: New Method Advances Knowledge about Smoking Cessation
Technological advances such as smart phones have facilitated the collection of intensive longitudinal data (ILD) in prevention science research. In a new article titled "Using the Time-Varying Effect Model (TVEM) to Examine Dynamic Associations Between Negative Affect and Self Confidence on Smoking Urges: Differences Between Successful Quitters and Relapsers" appearing in the journal Prevention Science, the authors demonstrate the advantage of applying TVEM to ILD. TVEM is a flexible approach to exploring the effects of covariates on a longitudinal outcome, where the effects are allowed to vary with time. For example, a person's mood might impact his/her urge to smoke immediately after quitting, whereas that impact may lessen with time during a successful quit attempt.
Read more.
Download the TVEM software (see below). |
New Software for Ecological Momentary Assessment (EMA) Data
We are pleased to release the TVEM (time-varying effect model) SAS macro suite. These macros can accommodate a wide variety of longitudinal outcomes: normally distributed, logistic-distributed, Poisson-distributed (count), and outcomes with zero-inflated Poisson distributions.
The TVEM SAS macro suite is an excellent tool for estimating the coefficient functions in TVEMs for intensive longitudinal data (longitudinal data such as EMA, characterized by more frequent measurements than traditional panel data). Traditional analytic methods assume that covariates have constant effects on a time-varying outcome. The TVEM SAS macros allow the effects of covariates to vary with time. These macros allow researchers to answer a broad array of research questions about how relationships change over time.
Download the macro suite.
Not familiar with SAS macros? View our 4-minute video on how to run a macro.
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Podcast: Adaptive Health Interventions and Causal Inference
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Daniel Almirall, Ph.D. |
In our latest podcast, host Aaron Wagner interviews Daniel Almirall, Faculty Research Fellow at the University of Michigan's Institute for Social Research and Research Investigator at The Methodology Center. The discussion focuses on sequential, multiple-assignment, randomized trials (SMARTs), which allow scientists to develop adaptive interventions. Danny works with Susan Murphy, the creator of SMARTs, to develop and promote this new methodological tool. Danny's work on causal inference is also discussed.
Download the podcast.
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