Stephen E. Fienberg

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 models appropriate for the analysis of ordinal variables, and for estimating the size of populations (especially in the context of census taking), Bayesian approaches to the analysis of contingency tables, and applications of these and related methods to the problem of data disclosure avoidance and confidentiality.

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, formal parallels in the design and analysis of sample surveys and randomized experiments, and the intertwined history of the two fields.

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.

Some Related Publications

Darroch, J.N., Fienberg, S.E., Gloneck, G.F.V., and Junker, B.W. (1993). A three-sample multiple-recapture approach to population estimation with heterogeneous catchability, Journal of the American Statistical Association, 88, pp. 1137-1148.

Fienberg, S. E. and Finkelstein, M.O. (1996). Bayesian statistics and the law, (J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith, eds.), in Bayesian Statistics , 5, Oxford University Press, (1996), pp. 129-146.

Fienberg, S.E. and Tanur, J. (1996). Reconsidering the fundamental contributions of Fisher and Neyman on experimentation and sampling, Int. Statist. Rev., 64, in press.

Fienberg, S.E., Makov, U. and Steele, R.J. (1996). Statistical notions of data disclosure avoidance and their relationship to traditional statistical methodology: Data swapping and loglinear models. Proceedings of the U.S. Bureau of the Census Twelfth Annual Research Conference.