Stephen E. Fienberg
Current research interests: analysis of categorical data; Bayesian approaches to confidentiality and data disclosure; causation; foundations of statistical inference; history of statistics; sample surveys and randomized experiments; statistics and the law; inference for multiple-media data.
My principal research interests lie in the development of statistical methodology, especially for problems involving categorical variables. Initially, I worked on the general statistical theory of loglinear models for categorical data, and I applied the theory to various problems that could be represented in the form of multidimensional contingency tables. More recently, I have studied approaches appropriate for disclosure limitation in multidimensional tables and their relationship with results on bounds for table entries given a set of marginals, estimating the size of populations (especially in the context of census taking), and Bayesian approaches to the analysis of contingency tables.
For several years now, I have also worked on the development of statistical methods for large-scale sample surveys such as those carried out by the federal government. This work (much of which has been in collaboration with Judith Tanur) has included the study of nonsampling errors, the use of surveys to adjust census results for differential undercount, cognitive aspects of the design of survey questionnaires, statistical analysis of data from longitudinal surveys, and formal parallels in the design and analysis of sample surveys and randomized experiments. My recent book with Margo Anderson, Who Counts? (which may appear shortly in a revised paperback edition), chronicles the story of the 1990 decennial census and efforts to use sample to adjust census results for differential undercount.
I have also been active in the application of statistical methods to legal problems and in assessing the appropriateness of statistical testimony in actual legal cases, and I have linked my interests in Bayesian decisionmaking to the issues of legal decisionmaking.
For several years now, I have also worked on methods for the analysis of non-numerical data, in the form of pictures, images, video, sound, symbols, and text. My work on statistical methods for multiple-media data is part of a larger research effort that is taking place in Carnegie Mellon's Center for Automated Learning and Discovery (CALD).
Some Related Publications
Bishop, Y.M.M., Fienberg, S.E., and Holland, P.W. (1975). Discrete Multivariate Analysis: Theory and Practice. M.I.T. Press, Cambridge, MA. Paperback edition (1977). A Citation Classic.
DeGroot, M.H., Fienberg, S.E., and Kadane, J.B., eds. (1986). Statistics and the Law. Wiley, New York. Wiley Classics Paperback edition (1994).
Fienberg, S.E., ed. (1989). The Evolving Role of Statistical Assessments as Evidence in the Courts. Springer-Verlag, New York.
Fienberg, S.E., Hoaglin, D.C., Kruskal, W.H., and Tanur, J.M., eds. (1990). A Statistical Model: Frederick Mosteller's Contributions to Statistics, Science, and Public Policy. Springer-Verlag, New York.
Devlin, B., Fienberg, S.E., Resnick, D.P., and Roeder, K., eds. (1997). Intelligence, Genes, & Success: Scientists Respond to The Bell Curve. Copernicus (Springer-Verlag), New York.
Anderson, M. and Fienberg, S.E. (1999). Who Counts? The Politics of Census-Taking in Contemporary America. Russell Sage Foundation, New York. Revised paperback edition (2001) in press.
Fienberg, S.E. (2000). "Contingency tables and log-linear models: Basic results and new developments," Journal of the American Statistical Association, 95, 643-647.
Anderson, M., Daponte, B.O., Fienberg, S.E., Kadane, J.B., Spencer, B.D., Steffey, D. (2000). "Sample-based adjustment of the 2000 census--A balanced perspective," Jurimetrics, 40, 341-356.