New Resource for Learning TVEM

simulated TVEM graphicMay 10, 2019:

Our newest resource helps scientists teach themselves how to use our time-varying effect modeling (TVEM) SAS macro. TVEM allows scientists to understand how associations between variables change over time. The TVEM Learning Path is designed to allow SAS users to efficiently teach themselves how to prepare data for, plan, and run a TVEM.

The Learning Path allows users to select from a variety of educational resources including videos, presentation slides, webpages, and hands-on SAS exercises. This format allows users to access the specific content they need in the format they desire to develop their skills as quickly as possible. Content is divided into

  • Conceptual introduction,
  • Detailed introduction,
  • Running a SAS macro,
  • Flipping data from long format to wide format,
  • Preparing to run a TVEM,
  • Running a TVEM,
  • Plotting results, and
  • Running the Weighted TVEM SAS macro.

We hope the Learning Path is useful and can be applied to other methods. Please send any thoughts, suggestions, or questions about the Learning Path to

Open the TVEM Learning Path.

Join Us at SPR!

April 30, 2019:

Join us at the Society for Prevention Research (SPR) 2019 Annual Meeting, May 28 through 31 in San Francisco. Methodology Center researchers will present symposia, talks, posters, a technical demonstration, and participate in the SPR Cup. We hope to see you there! Below is a list of the places where you can find us.

Tuesday, May 28

5:30 – 7:00 p.m. Poster Session I

  • “Heavy drinking and academics: Daily-level associations, or do less serious students just drink more?” Hannah Allen
  • “Profiles of dysregulation moderate the impact of preschool teacher-student relationships on later school functioning” Benjamin Bayly
  • “Identifying substance use disorders among individuals with spinal cord injury: Using big data Sources via electronic health records” Scott Graupensperger
  • “Effects of a mindfulness training intervention on alcohol use in public school teachers” Natalia Van Doren

Wednesday, May 29

1:15 – 2:45 p.m. Roundtable: Enhancing the reach and impact of drug abuse and behavioral health preventive interventions: Mining existing data for bold new discoveries Stephanie Lanza, Discussant

5:45 – 7:00 p.m. Poster Session II

  • “Approaches to characterizing drinking episodes in college students from wearable alcohol sensors” John Felt
  • “Gender differences in the time-varying association between cigarette use and weight concerns across adolescence” Anna Hochgraf
  • “Drug use patterns among young men of color who have sex with men” Eric Layland

7:00 –8:30 MOST-ly Mingling Join Kate Guastaferro in the Eclipse Kitchen & Bar, located in the lobby of the Hyatt Regency San Francisco, to socialize and discuss issues related to the optimization of interventions.

Thursday, May 30

10:15 – 11:45 a.m. Organized Paper Symposium: Opioid and other nonmedical prescription drug use in the United States: Contemporary trends in use, co-use, and correlates to identify opportunities for prevention Stephanie Lanza, organizer

  • “Contemporary trends in nonmedical prescription drug use as a function of individual and sociodemographic characteristics: Ages 12 to 90” Stephanie Lanza
  • “Age-varying trends in co-use of marijuana and heavy episodic drinking: Implications for nonmedical prescription drug use” Ashley Linden-Carmichael

10:15 – 11:45 a.m. Sloboda and Bukoski Cup Team:  Hannah Allen, Andrew Dismukes, John Felt, Natalia Van Doren, and Adrienne Woods

10:15 – 11:45 a.m. Roundtable Discussion: SPR task force on reducing health disparities and improving equity through prevention Bethany Bray, Discussant

3:00 – 4:30 p.m. Individual paper presentations: Prevention related to drug abuse across developmental stage Bethany Bray, Moderator

3:00 – 4:30 p.m. Individual paper presentations:Family, individual, and neighborhood risk factors as predictors of long-term behavior and mental health problems 

  • “Constellations of family risk and long-term adolescent antisocial behavior: A latent profile analysis” Emily LoBracio

6:40 – 7:55 p.m. Poster Session III

  • Technology Demonstration: Software, instructional materials, videos, and other resources from The Methodology Center at Penn State Bethany Bray

Friday May 31

8:30 – 10:00 a.m. Organized Paper Symposium: Applying latent class models in prevention science: Practical solutions to everyday problems Bethany Bray, Organizer

  • “Multiple imputation of missing covariate information in latent class analysis: evaluation of a step-by-step approach” John Dziak
  • “Multilevel latent profile analysis for daily diary data: Understanding triadic family dynamics” Mengya Xia
  • “Combining latent class analysis and time-varying effect modeling: Understanding the epidemiology of alcohol use” Bethany Bray

8:30 – 10:00 a.m. Individual Paper Presentations: using mobile health techniques to understand and prevent substance use

  • “Day and within-day trends of drug cravings: Ecological momentary assessment among a sample of patients with prescription opiate dependence” Jamie Gajos

10:15 – 11:45 a.m. Plenary Session III, Mobile health (mHealth) in prevention science: Assessment, intervention, and analysis Stephanie Lanza, Chair

1:00 – 2:30 p.m. Plenary Session III Roundtable: Mobile health (mHealth) in prevention science: Assessment, intervention, and analysis Stephanie Lanza, Chair

2:45 – 4:15 p.m. Organized Paper Symposium: Using time-varying effect models to understand predictors of substance use and depression within-days and across developmental periods Benjamin Bayly, Organizer

  • “Age-varying association between childhood maltreatment and depression and substance use” Yuen Wai Hung
  • “Age-varying effects of parental warmth and closeness on adolescent and young adult substance use and depression” Benjamin Bayly

Summer Institute on Mixed-Effects Location Scale Modeling

January 28, 2019:

We are pleased to announce that Donald Hedeker will present this year’s Summer Institute on Innovative Methods, “Variability in Intensive Longitudinal Data: Mixed-Effects Location Scale Modeling.” During the Summer Institute, Don will provide attendees with the theoretical background and applied skills necessary to use basic two- and three-level mixed models, as well as extended mixed models for the analysis of intensive longitudinal data (ILD). A major focus of the workshop will be on the modeling of variances from ILD.

The Summer Institute will be held June 17 – 18, 2019 on Penn State’s University Park Campus. The Institute is sponsored by Penn State’s Methodology Center and the National Institute on Drug Abuse.

Read more or apply to attend.

Video: Webinar on Multilevel Modeling

January 09, 2019:

This is a video of the webinar on multilevel modeling (MLM) for intensive longitudinal data that Methodology Center Investigator Michael Russell presented on November 14, 2018. The video includes both the presentation and the question-and-answer session that followed. Portions of the video were re-recorded due to audio problems with recording of the original webinar. The video is a great way to get started with MLM for intensive longitudinal data.
MLM is an extension of linear regression that adjusts for the statistical dependence that occurs when multiple observations are collected from each individual. It also allows the separation of within- and between-person associations. MLM is a powerful and flexible approach that allows users to specify a wide range of models and address diverse research questions using ILD. .

Watch our website and eNews for information about upcoming 1 & 1 webinars.

Watch the video on YouTube.

Free Webinar on Multilevel Modeling

September 10, 2018:
Join our upcoming 1 & 1 workshop, when Methodology Center Investigator Michael Russell will present an introduction to multilevel modeling (MLM) for intensive longitudinal data. 1 & 1 workshops consist of a one-hour live video presentation on a method followed by a one-hour question-and-answer session with the presenter. The workshop will be held on Wednesday, November 14, from 3:00 to 5:00 p.m. Eastern Time.

MLM is an extension of linear regression that adjusts for the statistical dependence that occurs when multiple observations are collected from each individual. It also allows the separation of within- and between-person associations. MLM is a powerful and flexible approach that allows users to specify a wide range of models and address diverse research questions using ILD. Michael will introduce MLM as a tool for answering questions about the within-person and between-person processes linking contextual and psychosocial factors to substance abuse risk.

The 1 & 1 will be hosted via Zoom webinar at Contact if you have any questions. We hope you will join us.

TVEM Teachers’ Corner: New Resource for Teaching a Methods Course

July 26, 2018:

teacherbox2The TVEM Teachers’ Corner provides resources for instructors who want to incorporate instruction on time-varying effect modeling (TVEM) into methods courses. The download will enable instructors to easily include a presentation and an exercise about TVEM into a class session. The TVEM Teachers’ Corner includes a PowerPoint presentation, two introductory articles for instructors, a SAS exercise (and solution key), and a reading list for students. These items are designed to make comprehending and presenting TVEM as easy as possible.

We also have available a Teachers’ Corner for latent class analysis (LCA).

Download the Teachers’ Corner or read more.

Introduction to Time-Varying Effect Modeling (TVEM) for Graduate Students and Postdoctoral Researchers

June 12,2018:tvem for grads

​We are pleased to offer the workshop, “Understanding Age-Related Changes Using the Time-Varying Effect Model”. TVEM allows researchers use several types of data to model the way associations between variables change over time. The workshop will present the concepts and applications of TVEM in order to give Penn State graduate students and postdoctoral researchers an efficient way to assess TVEM’s potential for their research. Lunch will be included.

Addressing Age-Related Change Using the Time-Varying Effect Model
PRESENTERS: Stephanie Lanza, Director of The Edna Bennett Pierce Prevention Research Center and professor of Biobehavioral Health and Ashley Linden-Carmichael, assistant research professor of Biobehavioral Health
WHEN: Tuesday, July 24, 2018, 10 a.m. – 2 p.m.
WHERE: Bennett Pierce Living Center, 110 Henderson Building

Introduction to TVEM is co-sponsored by the Social Science Research Institute (SSRI), The Methodology Center, and The Edna Bennett Pierce Prevention Research Center and is part of SSRI’s Innovative Methods Initiative. The workshop is FREE and open to all graduate students at Penn State. Registration is required and space is limited. To register, email Tammy Knepp (

The four-hour workshop will include

  • a conceptual introduction to TVEM, a highly flexible approach to estimate dynamic associations between covariates and outcomes;
  • motivating examples modeling age-related changes in substance-use behavior and its correlates;
  • open discussion of how TVEM might be applied in your research; and
  • demonstrations in SAS with sample code to modify for future use.

Who should attend?
We encourage you to register if you are a Penn State graduate student or postdoctoral researcher who wishes to learn more about the way processes unfold over time, and who is interested in addressing questions about age-related change using data from cross-sectional or panel studies.

Questions? Contact Tammy Knepp (

Featured Article: TVEM to Examine Gender Differences in Drinking Behavior

April 4, 2018:tvem gender differences

Historically, studies of health behaviors such as drug and alcohol abuse have included far more male participants than female participants. This creates potentially serious gaps in the available scientific knowledge about how drug and alcohol abuse differs for males and females. In a recent article published in Statistical Methods in Medical Research, Methodology Center Investigator Runze Li, lead author Songshan Yang, and their collaborators apply time-varying effect modeling (TVEM) to understand gender differences in drinking behaviors across adolescence. The authors’ goal was to understand gender differences in development of alcohol-use patterns in order to facilitate the development of tailored intervention and prevention efforts.

To examine these gender differences, the authors applied TVEM to longitudinal panel data from the Michigan Longitudinal Survey. The sample included 699 participants who ranged in age from 12 to 26 throughout the study, with up to 15 observations per individual. They found that among both males and females, alcohol consumption increased in early adolescence at a similar rate. From middle adolescence to young adulthood, both groups continue to increase, but the rate of increase is much higher for males. Both males and females show decreased drinking after the age of 24, suggesting maturation that reduces drinking behavior.

The authors also applied TVEM to daily phone-survey data from 2022 adults in the National Survey of Midlife Development in the United States. They did this to demonstrate that TVEM is flexible enough for use with both multi-wave longitudinal studies and short-term studies with intensive data collection. Beyond substance abuse, TVEM is flexible and can be applied in many contexts to compare trajectories between groups.

Summer Institute on Analysis of Ecological Momentary Data

January 29, 2018:

We are pleased to announce that Stephanie Lanza and Michael Russell will present this year’s Summer Institute on Innovative Methods, “Analysis of Ecological Momentary Assessment Data Using Multilevel Modeling and Time-Varying Effect Modeling.” During the Summer Institute, Stephanie and Mike will provide attendees with the theoretical background and applied skills necessary to identify and address innovative and interesting research questions in intensive longitudinal data streams such as daily diary and ecological momentary assessment (EMA) data using multilevel modeling (MLM) and time-varying effect modeling (TVEM). By the end of the workshop, participants will have fit several multilevel and time-varying effect models in SAS and will have had the opportunity to fit and interpret preliminary models using their own data.

The Summer Institute will be held June 28 – 29, 2018 on Penn State’s University Park Campus. The Institute is sponsored by Penn State’s Methodology Center and the National Institute on Drug Abuse.

Read more or apply to attend.

Runze Li Receives Distinguished Achievement Award from ICSA

September 14, 2017:rli17
Congratulations to Methodology Center Principal Investigator Runze Li for winning the 2017 Distinguished Achievement Award from The International Chinese Statistical Association (ICSA). ICSA is recognizing Runze for his research on variable selection, nonparametric and semiparametric modeling, and modeling for computer experiments. ICSA also specifically noted his interdisciplinary research—including his work here at The Methodology Center—and professional service.

Runze Li is Verne M. Willaman Professor of Statistics at Penn State. The Distinguished Achievement Award joins a long list of accolades he has earned, including the 2016 Canadian Journal of Statistics award, the 2012 United Nations’ World Meteorological Organization Gerbier-Mumm International Award, and being named a “Highly Cited Researcher” every year since 2014. In his current research on variable selection and variable screening, he is developing methods to analyze genetic data with intensive longitudinal data. This work will allow scientists to identify which genetic, individual, and social factors predict drug abuse, HIV-risk behavior, and related health behaviors.

Stress-Related Drinking in College Linked to Future Alcohol Problems

August 24, 2017:Mike Russell

Many people consume alcohol at the end of a stressful day, but there are questions about the long-term consequences of this type of drinking. In a new article in Psychology of Addictive Behaviors, Methodology Center Investigator Michael Russell and his collaborators David Almeida and Jennifer Maggs analyzed intensive longitudinal data (ILD) from a daily diary study to determine what links may exist between stress-related drinking and future problems with alcohol use.

The authors analyzed data from the University Life Study (PI: Jennifer Maggs), which collected daily diary data on 744 college students during the first four years of their university education. Using multi-level models, the authors examined the relationship between stress and drinking in daily life across more than 49,000 days (totaling all days from all students), comparing students’ likelihood of drinking on high-stress days to their likelihood of drinking on low-stress days. The authors found that, compared to themselves, students were somewhat more likely to drink on a high-stress day than on a low-stress day, but that this likelihood varied greatly between students. Next, they examined how an individual’s tendency to drink when he/she is under increased stress might impact the likelihood that he/she may have indicators of a drinking problem later in college. The authors found that students whose drinking was more reactive to stressors—that is, students whose drinking increased more sharply on high- versus low-stress days—were at greater risk for alcohol problems during their fourth year of college than students whose drinking was less reactive to stressors.

This article demonstrates how within-person slopes from multilevel models, which characterize the relationship between dynamic factors such as stress and drinking for each individual, can be useful in predicting risk for public health-relevant outcomes, such as risk for alcohol problems in university students. Future research is needed to determine whether interventions focusing on stress management could help reduce rates of problem drinking in young adult populations.

Open the article. (Journal access required.)


Russell, M. A., Almeida, D., & Maggs, J. L. (in press). Stressor-related drinking and future alcohol problems among university students. Psychology of Addictive Behaviors.

Podcast: Michael Russell on Ambulatory Assessment

January 23, 2017:Mrussell

In our latest podcast, Methodology Center Research Associate Michael Russell discusses ambulatory assessment and his pilot project examining self-report data during heavy drinking. In the project, Michael is combining ecological momentary assessment (EMA) of self-reported alcohol use with continuous data from ankle bracelets that measure alcohol intoxication levels through contact with the skin. He is investigating the accuracy of using EMA self-reports as a proxy for such intoxication measures during real-world drinking episodes. He discusses his thoughts on the challenges and opportunities of such data collection, and talks about some of his research using these and other intensive longitudinal data (ILD).

Download the podcast

00:00  Introduction

00:33  Developing an interest in methods

03:07  Ambulatory assessments for understanding substance use

06:29  Examining the accuracy of self-report data on alcohol use

08:30  Practical issues with ambulatory assessment studies

10:09  Methodological issues with ambulatory assessment studies

13:36  Implications for working with IRBs

15:40  Future of ambulatory assessment