Upcoming Talk at NIH: Developing Behavioral Interventions

March 4, 2013:
lmc
As part of the “Mind the Gap NIH Seminar Series,” Methodology Center Director Linda Collins will give a talk at the National Institutes of Health (NIH) in Washington, D.C., on March 26, 2013, about using the multiphase optimization strategy (MOST) to develop behavioral interventions for smoking cessation, drug abuse prevention, treatment of obesity, promotion of physical activity, and other health-related behaviors.

The seminar is part of the NIH’s lecture series, titled “Medicine: Mind the Gap,” which explores issues at the intersection of research, evidence and clinical practice—areas in which conventional wisdom may be contradicted by recent evidence. The goal of the series is to engage the NIH community in thought-provoking discussions about their role in helping to guide today’s research.

Read more

Software: LCA Stata Plugin

February 25, 2013:plugin

The Methodology Center is pleased to announce our first software release compatible with Stata, the LCA Stata Plugin for conducting latent class analysis (LCA). The software is available for download free of charge from our software page. The LCA Stata Plugin is based on version 1.2.7 of PROC LCA (also developed by the Methodology Center) and includes the same functionality.

 

Features include:

  •  multiple-groups LCA
  • LCA with covariates (prediction of latent class membership)
  • posterior probabilities available in output
  •  sampling weights and clusters can be incorporated

The software now has a full users’ guide. Please email mchelpdesk@psu.edu with any questions.

Download the software or read more

Summer Institute on Latent Class Analysis (LCA)-

February 21, 2013:summer13

We are pleased to announce that Methodology Center Investigators Stephanie Lanza and Bethany Bray will present this year’s Summer Institute on Innovative Methods, “Introduction to Latent Class Analysis.”

Sponsored by the Methodology Center and the National Institute on Drug Abuse, the 18th Summer Institute will present the theoretical background and applied skills needed to address interesting research questions using latent class analysis (LCA). By the end of the workshop, participants will have fit preliminary latent class models to their own data. The institute will be held on June 27-28, 2013 at Penn State in State College, PA. Apply early; there are a very limited number of seats available.

Read more or apply.

Free Faculty Workshop on Causal Inference with Lunch

February 12, 2013:dcoff

PhD-level researchers at Penn State: do you want to learn about applying cutting-edge methods in your work but have trouble finding time? Try A Taste of Methodology, a semiannual workshop series for faculty with lunch included. The objective is to provide you an efficient way to assess a method’s potential for your research.

This semester’s workshop is “Propensity Score Methods for Causal Analysis,” presented by Methodology Center Principal Investigator Donna Coffman. The three-hour workshop will include an introduction to propensity score methods for causal inference in non-randomized data, examples, resources, and a discussion of how to apply these methods to your work. The workshop is FREE and open to all PhD-level scientists as Penn State.

The workshop will be on Thursday, May 2, from 10:30 a.m. – 1:30 p.m. at the Bennett Pierce Living Center, 110 Henderson Building. A Taste of Methodology is co-sponsored by the Social Science Research Institute (SSRI).

Read more about Donna’s work on causal inference

Spaces fill quickly. Email Tammy Knepp to register.

NIH Funding Announcement Calls for Sequential, Multiple Assignment, Randomized Trials (SMARTs)

January 17, 2013:
A new announcement from NIH seeks proposals that improve behavioral treatments for drug abuse, HIV, chronic pain, or related behaviors. PA-13-077 is sponsored by the National Institute on Drug Abuse (NIDA), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), and the Office of Behavioral and Social Sciences Research (OBSSR). This program announcement specifically solicits proposals featuring sequential, multiple assignment, randomized trial (SMART) designs because of SMART’s applicability to efficacy studies and to translating interventions into real world settings.

SMART, an experimental design method for building adaptive health interventions, was developed by Methodology Center Principal Investigator Susan Murphy and her collaborators. Adaptive health interventions allow clinicians to create treatment sequences that change based on a patient’s characteristics or responses to earlier treatments. Adaptive interventions can improve outcomes for patients who are not responding to early treatments while decreasing burden and costs for patients who become stable during treatment. We are pleased by NIH’s recognition of how SMART designs can improve treatments and outcomes for patients.

View the program announcement

Read more about SMART

Podcast: Using Propensity Scores in Causal Inference

April 13, 2012:dcoff
As a preview for the upcoming Summer Institute, we recorded a podcast with Donna Coffman, Methodology Center Principal Investigator, and Max Crowley, doctoral candidate, on how to use propensity scores in causal inference when a study is not randomized.

Donna will present “Propensity Score Methods for Causal Inference” at this year’s Summer Institute on Innovative Methods. The Institute will describe statistical, methodological, and conceptual aspects of propensity score methods for causal inference.  It will be held in State College,  PA, on June 21-22, 2012 at the Penn Stater Conference Center and Hotel. Scholarships are available to qualified applicants.

Download the podcast

Register for the Summer Institute

Selected Articles Related to this Podcast

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688-701. View abstract

Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516-524. View abstract

Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33-38. View abstract

Come see us at SPR!

April 11, 2011:

Society for Prevention Research (SPR)

Washington, DC, May 31-June 3, 2011

Dr. Linda Collins will be giving the presidential address for the conference: “Prevention in the 21st Century: Adapting Engineering Optimization Strategies to Create Leaner, Meaner, Better Interventions.”
The following talks will appear in the symposium, Innovations in Latent Class Analysis: New Approaches to Address Classic Questions, chaired by Bethany Bray:

  • SPR Presenters: Linda Collins, Stephanie Lanza, Runze Li, Donna Coffman, Shu Xu, Daniel Almirall, Mariya Shiyko, and Xianming Tan“Classify-Analyze Approaches in Latent Class Analysis: The Importance of Inclusive Modeling”: Bethany Bray, Stephanie Lanza, & Xianming Tan
  • “Latent Class Analysis with a Distal Outcome: Traditional and New Approaches”: Xianming Tan, Stephanie Lanza, & Bethany Bray
  • “Causal Inference in Latent Class Analysis”: Stephanie Lanza, Donna Coffman, Shu Xu, & Daniel Almirall

The following talks will appear in the symposium, Applications of Novel Methods for Analysis of Intensive Longitudinal Data in Studies on Drug Use, organized by Dr. Mariya Shiyko:

  • “Between-Group Differences in Temporal Dynamics of Negative Affect, Self-Confidence, and Smoking Urges in Short-Term Successful Quitters and Relapsers: Applications of the Model with Varying Effects (MOVE)”: Mariya Shiyko, Stephanie Lanza, Xianming Tan, Saul Shiffman, & Runze Li
  • “Effects of Beer Volume Tax on Alcohol-Related Mortality in 26 States from 1969 to 2004: An Application of a Varying Effects Model”: Mildred Maldonado-Molina, Xianming Tan, Stephanie Lanza, & Alexander Wagenaar
  • “Joint Modeling of HIV Disease Course and Survival: Effects of Alcohol, Tobacco, and Drug Use”: Stephanie Lanza, Xianming Tan, & Runze Li