Markov chain Monte Carlo (MCMC) methods, originating in computational physics about half a century ago, have seen an enormous range of applications in quantitative scientific investigations. This is mainly due to their ability to simulate from very complex distributions such as the ones needed in realistic statistical models. This talk provides an introductory tutorial of the two most frequently used MCMC algorithms: the Gibbs sampler and the Metropolis-Hastings algorithm. Using simple yet non-trivial examples, we demonstrate, via live performance, the good, bad, and ugly implementations. Along the way, we also reveal the secret behind the greatest statistical magic.
This talk and membership social is co-sponsored by the Boston Chapter of the American Statistical Association (serving members in Massachusetts, Vermont, New Hampshire and Maine).
In many epidemiologic studies, the first indication of an environmental or genetic contribution to the disease is the way in which the diseased cases cluster within the same family units. The concept of clustering is contrasted with incidence. New parametric generalizations of binomial sampling models are described to provide measures of the effect size of the disease clustering. We consider models and an example that takes covariates into account. Ascertainment bias is described and the appropriate sampling distribution is demonstrated.
Survival analysis is a branch of statistics that involves the modelling of time to event data. It is commonly used in the biomedical sciences, where the focus is on observing time to death or a health-related event. However, time to event analysis has also been used in the social sciences, where interest is on analyzing the time to job changes, marriage, and births. In the engineering sciences, the main focus is on modelling the time it takes for machines or electronic components to break down. This talk will give an overview of survival analysis, and provide an introduction to Kaplan-Meier curves and the Cox proportional hazards model. Oh and by the way, the median time to find a job is the lowest in 3 years.
Dr. Pace is also speaking about careers in the biotechnology sector at noon on February 13th as part of the pre-health series; contact Nicholas Horton for more information or to sign up.
Thanks to the Smith College Lecture committee, Department of Mathematics and Statistics, Office of the Dean of the Faculty and the Alumnae Association for support of the series.
Applied Statistics Lecture series (2005-2006)
Other 5 college seminars of interest:
University of Massachusetts Statistics and
Probability Seminar Series
Organized by Nicholas Horton.
Last updated July 30, 2007