News Archive

Donna Coffman

April 3, 2014

When parents know more about their teenage children’s activities, those children are less likely to engage in risky behavior (e.g., delinquency, substance use initiation). Though this connection is widely acknowledged, it is not clear whether the knowledge is the determining factor in the reduced risk, because many other factors are involved in the parent-child relationship. In a recent article in Prevention Science, the authors use propensity scores to examine the causal nature of this relationship. The research team includes former Penn State graduate student Melissa Lippold, Methodology Center Principal Investigator Donna Coffman, and Edna Peterson Bennett Endowed Chair in Prevention Research Mark Greenberg. 

LCA Stata Plugin

April 2, 2014

The Methodology Center is pleased to release the latest version (1.1) of the LCA Stata plugin for conducting latent class analysis (LCA). The software is available for download free of charge. For an overview of the functionality of the LCA Stata plugin, please visit the download page. The new version includes functionality requested in our recent software survey, including

  • the ability to assess identification of models with covariates via multiple random starts,
  • an indication of which latent class is the best match for each individual, and
  • the option to generate 20 random draws for each individual’s class membership based on posterior probabilities.

The users’ guide has also been updated and revised based on user feedback. Please email mchelpdesk@psu.edu with any questions.

 

Read more or download the software

Daniel Almirall and Billie Nahum-Shani

March 24, 2014

The application deadline for this year's Summer Institute on Innovative Methods, "Experimental Design and Analysis Methods for Developing Adaptive Interventions: Getting SMART" has been extended by one week. The new deadline is Monday, April 7.  

  

The institute will be presented by Daniel Almirall and Inbal Nahum-Shani, Methodology Center researchers at the University of Michigan. 

The workshop will focus on the sequential, multiple assignment, randomized trial (SMART) and its application for developing interventions that adapt to patient need. A limited number of scholarships are available.

  

The institute will be held June 19-20, 2014, at the University of Michigan in Ann Arbor, Michigan.    

  

Read more or apply.

Constantino LagoaMarch 5, 2014

In control engineering, devices continually monitor the performance of a system and then operate to control that system. Common examples include automobile thermostats and autopilot systems on commercial airliners. These same principles can be used to design behavioral interventions that adapt over time to help patients alter behaviors that affect their health. Potential applications include maintaining an exercise regimen, maintaining a healthy diet, or abstaining from tobacco or illicit drug use.

 

In a forthcoming article in the Journal of Consulting and Clinical Psychology, Methodology Center Investigators Constantino Lagoa, Stephanie Lanza, Susan Murphy, and their colleague Korkut Bekiroglu describe this new approach to building adaptive, intensive interventions. The authors show how data, in this case simulated smoking-cessation data, can be used to inform the design of an adaptive, intensive intervention by applying control-engineering techniques. This intervention, which is designed to provide treatment only when needed, is shown to improve effectiveness while decreasing patient burden. This approach holds great promise for informing clinical decisions and for informing the development of smartphone-based adaptive interventions. 

March 3, 2014

Thanks to all those who participated in our survey on software development! The results were very helpful to us. Here are a few highlights of what we learned.

 
SAS is the platform most respondents are using. This is not entirely surprising, considering we already develop in SAS. (It’s a little like asking Toyota owners what kind of cars they plan to buy.) Next most popular was R, then Stata. Of write-in candidates, SPSS and Mplus gathered the most votes. (Please note that Mplus is not an open program for development, however.)

 

R is gaining market share among our audience. R is the most popular second-choice platform. This is great news because R is free, which means that anything we develop for R is TRULY free to use, which is our preference. We will keep R in mind as we plan for the future.

Linda CollinsFebruary 27, 2014

We are pleased to announce that Penn State has named Linda M. Collins, director of The Methodology Center and professor of human development and family studies and of statistics, a distinguished professor for her research, leadership, and service.
 
Linda's research focuses on development of innovative research approaches to optimize behavioral interventions. She has been an important contributor to the field of prevention science through her work on preventing tobacco and other substance use. She is now extending her work into other public health areas such as obesity and HIV/AIDS. Linda has also developed methods for analysis of longitudinal data, particularly latent transition analysis.

Stephanie LanzaFebruary 26, 2014

We are pleased to announce this spring’s Taste of Methodology workshop: The time-varying effect model (TVEM) for analyzing intensive longitudinal data. Taste of Methodology is a series of brief workshops for Penn State faculty that offers an overview of innovative methods along with lunch. This semester’s workshop will present the concepts and applications of TVEM in order to give faculty an efficient way to assess TVEM’s potential for their research. 

 

 

A Taste of Methodology: The time-varying effect model (TVEM) for analyzing intensive longitudinal data

PRESENTER: Stephanie Lanza, Scientific Director of The Methodology Center

WHEN: Wednesday, May 7, 2014, 10:30 am - 1:30 pm

WHERE: Bennett Pierce Living Center, 110 Henderson Building

  

A Taste of Methodology is co-sponsored by the Social Science Research Institute and the Methodology Center, and is part of SSRI's Innovative Methods Initiative. The workshop is FREE and open to all Ph.D.-level scientists at Penn State. Registration is required and places are limited. To register, email Tammy Knepp (TLKnepp@psu.edu).

Daniel Almirall and Billie Nahum-ShaniFebruary 19, 2014

We are pleased to announce that Drs. Daniel Almirall and Inbal “Billie” Nahum-Shani, Methodology Center researchers at the University of Michigan, will be teaching this year’s Summer Institute on Innovative Methods, "Experimental Design and Analysis Methods for Developing Adaptive Interventions: Getting SMART.”

 

Sponsored by Penn State's Methodology Center and the National Institute on Drug Abuse, the 19th summer institute will introduce adaptive interventions; provide the background needed to plan a sequential, multiple assignment, randomized trial (SMART); and present the data analysis methods needed to construct adaptive interventions using SMART study data.

 

The institute will be held June 19-20, 2014, at the University of Michigan in Ann Arbor, Michigan. 

Read more or apply

PROC LCAJanuary 24, 2014

We have released PROC LCA v. 1.3.1 to fix a bug related to the seed_draws statement in v. 1.3.0 that sometimes causes an error. If you used seed_draws and did not receive an error message, then the output generated is reliable. There is no change in functionality between v. 1.3.0 and 1.3.1.

Download PROC LCA v. 1.3.1

qlaciJanuary 22, 2014

We are pleased to announce the release of the qlaci (Q-learning with adaptive confidence intervals) R package. This is a tool for designing an adaptive intervention using data from a sequential, multiple assignment, randomized trial (SMART). Interventions that adapt at the right times can improve participant outcomes (e.g., intensifying for people who do not respond to the initial treatment) while decreasing the cost and burden of the intervention (e.g., stepping down treatment for participants who respond). SMART designs provide the data needed to construct high-quality adaptive interventions.

 

Qlaci requires R 2.15. or higher, which is available for free download. This package is designed to work on Windows, Mac, or Linux operating systems. 

Read more about SMART

Download the software

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