May 15, 2013

It's been a good spring for Debashsis Ghosh, who has accepted an invitation to serve as chairperson of the Biostatistical Methods and Research Design Study Section at NIH's Center for Scientific Review for the next two years. Members of study sections are selected on the basis of their demonstrated competence and achievement in their scientific discipline as evidenced by the quality of research accomplishments, publications in scientific journals, and other significant scientific activities, achievements and honors.  Membership on a study section represents a major commitment of professional time and energy as well as a unique opportunity to contribute to the national biomedical research effort. The skill and leadership offered by the chairperson is an important factor in the effectiveness and efficiency of the review group.

May 6, 2013

Debashis Ghosh has been awarded the 2013 Mortimer Spiegelman Award. The award was created in 1970 by the Applied Public Health Statistics Section of the American Public Health Association (APHA) to honor a statistician, 40 years of age or younger, who has made outstanding contributions to health statistics, especially public health statistics. The award is presented annually at the APHA meeting, and it serves three purposes: to honor the outstanding achievements of both the recipient and Spiegelman, to encourage further public health involvement by the finest young statisticians, and to increase awareness of APHA and the Applied Public Health Statistics Section in the academic statistical community. The award will be presented at the 2013 APHA meeting in November.

April 5, 2013

As part of the “Medicine: Mind the Gap” NIH Seminar Series, Methodology Center Director Linda Collins  recently gave a talk at the National Institutes of Health (NIH) in Washington D.C. She discussed the multiphase optimization strategy (MOST) and how it can be used to optimize 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 lecture series that 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. This high-resolution video provides an excellent introduction to MOST.

Watch the video

Download the slides

March 28, 2013

Latent class analysis (LCA) is a tool used by behavioral scientists to identify subgroups within a population. When conducting LCA, choosing the number of classes (subgroups) in the model is a critical step. Some software, like the Methodology Center’s Bootstrapping Macro for PROC LCA, allows users to perform the bootstrap likelihood ratio test (BLRT) to evaluate models with different numbers of classes. Until now, however, there has been no way to determine the sample size needed to provide adequate power for the BLRT. In a new article by  John Dziak, Stephanie Lanza, and Xianming Tan to appear in Structural Equation Modeling, the authors provide effect-size measures and power curves that can be used to predict power for the BLRT in LCA.  These power curves can guide researchers in determining the sample size needed for their proposed LCAs.