Smith College Applied Statistics Lecture series (2011-2012)

1. Analysis of Partially-Observed Social Network Data
   Krista Gile, Department of Mathematics and Statistics
   University of Massachusetts Amherst
   Thursday September 29, 2011, noon, Burton Forum (3rd floor) (Clark Science Center), lunch provided, please bring your own drink.

   Human populations are often connected by social networks of relations.Such social networks may either be of direct interest to researchers, or useful in designing sampling strategies through which to reach population members. Most existing strategies for statistical inference focus on cases where the full social network is observed. In this talk, we present three cases in which the social network is only partially observed, and use these cases to highlight the variety of questions and approaches used in social network research. In the first case, we are interested in understanding the social connections of adolescents in a high school, in a setting in which data are missing because some adolescents did not complete the survey. In the second case, we aim to estimate features of disease transmission over a network of potentially disease-transmitting contacts, observed through a public health strategy known as 'contact tracing,' an intervention based on following high-risk links from known infected persons. In the final example, we are interested in estimating disease prevalence, the summary of an individual-level characteristic, from a variant of link-tracing network sampling known as 'Respondent-Driven Sampling.'We conclude by comparing the cases to reflect on the types of analysis possible with network data.

2. Finding Genetic Markers for Disease: Some Challenges and Opportunities for Biostatisticians
   Nan Laird, Department of Biostatistics
   Harvard School of Public Health
   Thursday, March 15th, 2012, 5:00pm, McConnell B15 (Clark Science Center), tea from 4:30pm in Burton Forum (3rd floor). All are invited.

   In the relatively short time span of less than 10 years, association analysis has become the primary study design for finding genes underlying complex disorders. Genome Wide Association Studies have discovered hundreds of new genetic markers which predict disease. Early successes with association analysis (Macular Degeneration and Crohn’s Disease) led to great excitement about the promise of GWAS for understanding the genetic basis of complex disease. Although the number of GWAS studies has proliferated rapidly, replications are often disappointing and Meta-Analysis has become an essential part of the process of gene discovery. This talk will review some features of GWAS that offer challenges and opportunities for Biostatisticians.

Thanks to the Department of Mathematics and Statistics and the Center for Women in Mathematics for support of the series.

Applied Statistics Lecture series (2010-2011)

Other 5 college seminars of interest:
University of Massachusetts Statistics and Probability Seminar Series

University of Massachusetts Biostatistics and Epidemiology Seminar Series

Organized by Nicholas Horton.
Last updated March 6, 2012