American Statistical Association
New York City
Metropolitan Area Chapter

The Levin Lecture Series
Department of Biostatistics
Columbia University



ANALYTIC INFERENCE FOR DATA FROM COMPLEX SURVEYS

by

Jean Opsomer, Ph.D.
Chair and Professor, Department of Statistics
Colorado State University
www.stat.colostate.edu/~jopsomer/

Host: Dr. Qixuan Chen


Abstract

Surveys are an important source of data in many social, health and environmental sciences. When analyzing datasets that were obtained through surveys, failure to take the design aspects into account can lead to invalid estimation and inference, even when the mode of inference is model-based. We begin by describing some of the issues associated with informativeness in analytic inference, and examine the differences between model-based and design-based modes of interference. We then describe a number of new results and approaches in testing and adjusting for design effects, using a combination of parametric and nonparametric tools.

Biographical Note

Originally, from Belgium, I have an MBA from the University of Chicago. I obtained my PhD in Operations Research at Cornell University. After 12 years in the Department of Statistics at Iowa State University, I moved to the Department of Statistics at Colorado State University in 2007, and I have been the department Chair since January 2011. I am a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. I am currently the Chair of the ASA Nonparametric Section, and I am a member of the Executive Committee of the Institute of Mathematical Statistics. My research interests are in survey statistics, nonparametric statistics and environmental statistics.


Date: Thursday, November 3, 2011
Time: 4:00 - 5:00 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Biostatistics Computer Lab
6th Floor - Room 656
New York, New York

RESERVATIONS ARE NOT REQUIRED

Informal tea at 3:40 P.M.


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