Social Science Statistics Blog

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2 October 2006

Applied Statistics –Subharup Guha & Louise Ryan

This week the Applied Statistics Workshop will present a talk by Subharup Guha, Post-Doctoral Research Fellow in the Harvard School of Public Health Department of Biostatistics, and Louise Ryan, Henry Pickering Walcott Professor of Biostatistics in the Harvard School of Public Health and Department of Biostatistical Science at the Dana-Farber Cancer Institute.

Before coming to Harvard, Dr. Guha received his Ph.D. in Statistics at Ohio State University. Dr. Guha’s publications appear in Environmental and Ecological Statistics, Journal of the American Statistical Association, Journal of Computational and Graphical Statistics and the Journal of the Royal Statistical Society. His research interests include Bayesian modeling, computational biology, MCMC simulation, Semiparametric Bayesian methods, Spatio-temporal models and survival analysis.

Professor Ryan earned her Ph.D. in Statistics from Harvard University, and has been a member of the Department of Biostatistics since then. She has received numerous honors and distinctions during that time including the the Spiegelman Award from the American Public Health Association, and was named Mosteller Statistician of the Year. She has published extensively in Biometrics, Journal of the American Statistical Association, Journal of Clinical Oncology, and the New England Journal of Medicine. Her research interests focus on statistical methods related to environmental risk assessment for cancer, developmental and reproductive toxicity and other non-cancer endpoints such as respiratory disease, with a special interest in the analysis of multiple outcomes as they occur in these applied settings.

Dr. Guha and Professor Ryan will present a talk entitled "Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates." The paper that accompanies the talk is available from the course website. The presentation will be at noon on Wednesday, October 4th, in Room N354, CGIS North, 1737 Cambridge St. Lunch will be provided.

Posted by Eleanor Neff Powell at 12:02 PM

It Takes Two (Non-Motown Version)

The New York Times recently published an obituary for David Lykken, who was a pioneer of twin studies. His “Minnesota Twin Studies” suggested the importance of genetic factors in life outcomes. But his work with twins also spurred empirical research in many fields, not just genetics – and for good reason.

The idea of using twins for social science studies is very appealing: some twins are genetically identical, and also grow up in the same family and environment. So from a statistical perspective, comparing outcomes such as earnings between pairs of twins is like having a “perfect match." This idea made the rounds in many fields, such as labor economics. By using the argument that all unobserved characteristics (e.g. “genetic ability”) should be equal and can thus be differenced away, twin studies were used to estimate the returns to education – the effect of education on wages.

Alas there are potential problems with using twin data. For example, measurement error in a difference estimation can lead to severe attenuation bias precisely because twins are so similar. If there is little variation in educational attainment, even small measurement errors can strongly affect the estimate. Researchers have been ingenious about this (e.g. by instrumenting one persons’ education with the level that her twin reported, as in Ashenfelter and Krueger). While this may reduce the attenuation bias it can magnify the omitted variables bias which motivated the use of twins in the first place. Because there are only small differences in schooling, small unobserved differences in ability can lead to a large bias. The culprits can be details such as differences in birth weight (Rosenzweig and Wolpin have a great discussion of such factors). In addition, twins who participate in such studies are a selected group: they are getting along well enough to participate, and many of them get recruited at “twin events.” But not all twins party in Twinsburg, Ohio.

Of course none of this is to belittle the contribution of Dr Lykken, who besides helping to start this flurry of work also was also a major contributor to happiness research.

Posted by Sebastian Bauhoff at 1:10 AM