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The American Statistical Association (ASA)

The Statistical Partnerships Among Academe, Industry & Government Committee (SPAIG)

Committee Link

Charge

Identify, lead, and promote initiatives that foster partnerships between academe and business, industry, & government (B/I/G), which would include the following:

(1) Establish a partnership award recognizing successful partnership efforts between academe and B/I/G.

(2) Promote periodic JSM sessions that focus on partnership case studies and other relevant partnering.

(3) Recommend and support periodic salary surveys of B/I/G statisticians.

(4) Maintain a SPAIG web site to communicate partnership activities, progress on SPAIG initiatives, the partnership award program, and other SPAIG information.

 

 

Breaking News

The SPAIG Award Reinstated!

April 12, 2016

      The Statistical Partnerships Among Academe, Industry & Government (SPAIG) Award has just been reinstated by the ASA Board of Directors! The nomination process will take place by early 2017, and the upcoming SPAIG Award will be presented at the Joint Statistical Meetings in 2017, from July 29 to August 3, 2017, Baltimore, Maryland, USA. More details will follow!

      The previous SPAIG Award was presented in 2012, with the following citation: "The SPAIG Award The ASA established the SPAIG Award in 2002 to recognize outstanding partnerships established between academe and business, industry, and government organizations and to promote new partnerships. It is the only ASA award that recognizes organizations. The 2012 SPAIG award will be given to the following organizations: Baylor University and Eli Lilly & Company in recognition of the vision and support provided by Eli Lilly to Baylor University in the creation of a partnership for the enhancement of pharmaceutical research and development."

      Thank you for your attention!

      Sincerely,

The ASA SPAIG Committee

Email: SPAIG.ASA@gmail.com

Past SPAIG Awardees and Their Citations 

 

 

Shared Experiences in "AmStat News"

Top 10 Tips for Getting Successful Statistical Internships

Link to the Article

If you are a graduate or advanced undergraduate student in statistical sciences and related fields, these 10 tips may increase your likelihood of getting an internship. Once you have secured and completed an internship, it will be a valuable lifelong experience. 

Internships Make Such a Difference: The Experiences of Four Students

Link to the Article

Ruobin Gong, PhD Student, Harvard University

Tyler G. Kinzy and James P. Normington, Master’s Students, University of Minnesota

Steven Willke, Undergraduate Student, The Ohio State University 

A Recipe for Successful Collaborations: A JSM 2015 Panel Discussion

Link to the Article

Six distinguished statisticians, herein the “panel,” from various professional sectors offered valuable thoughts and advice on how statisticians may form vital collaborations across sectors. This session had a wide appeal, given the increasing focus on inter-disciplinary research and the emergence of complex and high dimensional big data as such challenges are common across all sectors. The discussion was extremely valuable to statisticians across diverse areas of statistical practice, especially to those in smaller institutions or organizations for whom collaborations may not have existed when they joined. 

 

 

JSM 2016 SPAIG Luncheon

Featuring Professor Donald Hedeker, The University of Chicago

(Please Reserve Your Ticket Early)

Session Link

 

Date/Time: Sunday, July 31, 2016 : 12:30 PM to 1:15 PM

Title: Modeling Means and Variances Using Mixed Effects Location Scale Models for Intensive Longitudinal Data

Speaker: Professor Donald Hedeker, University of Chicago

Link to the Speaker's Biographical Information

Abstract: Intensive longitudinal data are increasingly encountered in many research areas. For example, ecological momentary assessment (EMA) and/or mobile health (mHealth) methods are often used to study subjective experiences within changing environmental contexts. In these studies, up to 40 observations are usually obtained for each subject over a period of a week or so, allowing one to characterize a subject's mean and variance and specify models for both. In this presentation, we focus on an adolescent smoking study using EMA where interest is on characterizing changes in mood variation. We describe how covariates can influence the mood variances and extend the statistical model by adding a subject-level random effect to the within-subject variance specification. This permits subjects to have influence on the mean, or location, and variability, or (square of the) scale, of their mood responses. Models for both continuous and ordinal outcomes are described and illustrated with examples. These mixed-effects location scale models have useful applications in many research areas in which interest centers on the joint modeling of the mean and variance structure.

Keywords: heterogeneity; mixed-effects models; variance modeling

 

 

JSM 2016 SPAIG Session

Research-Oriented Internships

Session Link

Date/Time: Wed, 8/3/2016, 8:30 AM - 10:20 AM

Session Title: Effective Research-Oriented Internships: Fostering the Next Generation of Statisticians

The Summer Internship Partnership of ASA and Novartis Oncology: a Multi-Win Endeavor

Link to the Abstract

Authors: William Mietlowski, Novartis Pharmaceuticals Corp.; Rebecca Nichols, American Statistical Association; Linda Finelli, Novartis Pharmaceuticals Corp.

Internships as Training for MS Level Statisticians

Link to the Abstract

Author: John E. Kolassa, Rutgers, the State University of New Jersey

Capturing Carryover Effects in Crossover Designs in the Absence of Non-Crossover Sequences

Link to the Abstract

Authors: Vladimir Geneus, Department of Statistics; Ed P. Whalen, Pfizer; Ching-Ray Yu, Pfizer Inc.; Samaradasa Weerahandi, Pfizer; Chunming (Mark) Li, Pfizer

Inference on Ratios of Correlated Variables with Applications to Dietary Quality Assessment

Link to the Abstract

Authors: Aiyi Liu, NICHD/NIH; Xiaoyu Cai, George Washington University; Zhaohai Li, George Washington University

Discussant: Wei Shen, Eli Lilly and Company

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