News Archive | The Methodology Center

News Archive

December 18, 2014

Runze LiCongratulations to Runze Li who was recently named the Verne M. Willaman Professor of Statistics at Penn State! Runze is an influential and productive researcher, a great mentor, a supportive and helpful colleague, and a delightful person. We are proud and honored to have him as part of our Center. His recent work has focused on time-varying effect models (TVEMs) and the analysis of high-dimensional data. His work on TVEM is helping answer new questions about relationships over time. His work on high-dimensional data is laying the groundwork for incorporating genetic data into behavioral research.

Read more about TVEM

Read more about High-Dimensional Data Analysis

December 3, 2014

Rebecca Evans-PolceIn the United States, rates of substance use peak during adolescence and young adulthood. Previous literature has demonstrated that rates differ by race, ethnicity, and gender. Despite knowledge of these disparities, until now researchers have been unable to understand the extent to which these disparities change across adolescence and young adulthood. In the forthcoming article, “Changes in gender and racial/ethnic disparities in rates of cigarette use, regular heavy episodic drinking, and marijuana use: Ages 14 to 32,” to appear in Addictive Behaviors, Methodology Center researchers Rebecca Evans-Polce, Sara Vasilenko, and Stephanie Lanza use the time-varying effect model (TVEM) to examine the dynamic nature of substance use rates among different groups of adolescents and young adults.


December 1, 2014

Runze LiCongratulations to Runze Li for being named a Highly Cited Researcher by Thomson Reuters. This means that Runze is in the top one percent of most cited researchers in his field. Runze’s research focuses on the analysis of intensive longitudinal data (ILD) and high-dimensional data. During his 12 years as an investigator at The Methodology Center, Runze has been a pioneer not only in developing statistical methods but also in disseminating those methods to behavioral researchers. He led the development of the TVEM macro suite and the FHLM-LLR macro for analyzing ILD and PROC SCADLS & PROC SCADGLIM for selecting variables in high-dimensional data. Runze’s work is becoming even more relevant with the increasing availability of high-dimensional data, such as genetic data and ILD, such as data from smartphone studies. We look forward to many more years of collaborating with Runze.


Read about Runze’s research on analyzing ILD

November 10, 2014

Donna CoffmanPrevious literature has established that gang membership is associated with higher rates of drug use. In the forthcoming article, “Gang membership and substance use: Guilt as a gendered causal pathway,” in The Journal of Experimental Criminology, Methodology Center Investigator Donna Coffman and two other researchers examine whether anticipated guilt for substance use explains this association. The authors also expand the available set of methods for causal inference when assessing mediation in the presence of moderation and time-varying confounding.  

November 4, 2014

Susan MurphyIn our latest podcast, Amanda Applegate interviews Susan Murphy, Methodology Center principal investigator, Herbert E. Robbins Distinguished University Professor of Statistics, research professor at the Institute for Social Research, and professor of psychiatry at the University of Michigan. The discussion focuses two topics, the sequential, multiple assignment, randomized trial (SMART), which allows scientists to develop adaptive interventions, and the just-in-time, adaptive intervention (JITAI), which uses real-time data to deliver interventions as needed via mobile devices. Susan’s MacArthur Fellowship is also discussed; the podcast was recorded before she was elected to the Institute of Medicine of the National Academies.


November 3, 2014

output graphWe are pleased to release the latest version of the TVEM (time-varying effect model) SAS macro suite (v. 2.1.1). The macros in this suite estimate the coefficient functions in TVEMs for intensive longitudinal data (longitudinal data such as ecological momentary assessments, EMA, that are 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 enable researchers to answer new research questions about how relationships change over time. The newest version of the software includes some minor usability improvements.


Download the macro suite.

Not familiar with SAS macros? View our 4-minute video on how to run a macro.

October 21, 2014

Susan MurphyWe are delighted to announce that Methodology Center Principal Investigator Susan A. Murphy has been named a member of the Institute of Medicine (IOM) of the National Academies. Susan’s record of innovation, particularly her development of the sequential, multiple assignment, randomized trial (SMART), has earned her many recent accolades, including a MacArthur Foundation “genius” award in 2013.


IOM is an independent, nonprofit organization. Members of the Institute seek to provide the best available evidence on matters related to health to inform decision making on medical matters by the government and public. Being named to the Institute of Medicine is a huge honor for any scientist working on public health issues. In 2011, The New York Times said, “The Institute of Medicine is the nation’s most esteemed and authoritative adviser on issues of health and medicine, and its reports can transform medical thinking around the world.”

October 20, 2014

MD2K Center for Excellence logoFour Methodology Center affiliated scientists, Susan Murphy, Inbal Nahum-Shani, David Conroy, and Bonnie Spring, are part of a new research center, the MD2K Center for Excellence for Mobile Sensor Data-to-Knowledge. MD2K’s mission is to develop tools and methods to gather and analyze data from mobile devices in order to facilitate the early detection and prevention of health problems. The new center is funded through the National Institutes of Health (NIH) new Big Data to Knowledge initiative, which is also supporting Methodology Center Investigator Donna Coffman’s career development award


October 9, 2014

Donna CoffmanCongratulations to Methodology Center Investigator Donna Coffman, who received a K01 Career Development Award from the National Institutes of Health Big Data to Knowledge initiative! The award will fund 100% of Donna’s training and independent research for the next three years. Donna’s work will focus on the analysis of big data to promote healthy behavior related to physical activity, diet, stress management, and substance use.
K awards include a training component, and Donna will study methods from computer science and informatics in order to manage and analyze big data. She will study statistical methods for the integration and analysis of big data, including genomics data, ecological momentary assessments, and data from wearable devices.


September 26, 2014

Mark Stemmler

Mark Stemmler, professor of psychological assessment at the University of Erlangen-Nuremberg, Germany, has written a new book, Person centered methods: Configural frequency analysis (CFA) and other methods for the analysis of contingency tables. 


Mark is a long-time friend of The Methodology Center, and last month, he visited us from Germany to teach one of our one-credit graduate courses. While he was here, Mark sat down with the Methodology Center’s science writer, Aaron Wagner, to briefly chat about Mark’s new book and the value of CFA.


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