Joseph B Lang

Joseph B Lang
Professor of Statistics and Actuarial Science, College of Liberal Arts and Sciences
Chair (Jan 2015-Aug 2019), Department of Statistics and Actuarial Science, University of Iowa, January 2015 - August 2019

Contact Information

Primary Office: 207 Schaeffer Hall


Joseph B. Lang is Professor in the Department of Statistics and Actuarial Science, at the University of Iowa. He is a fellow of the American Statistical Association and an associate editor of Statistical Modelling: An International Journal. His current research includes work on categorical data methods, causal inference, randomization tests, missing data, and fiducial inference.


  • PhD in Statistics, University of Florida, Gainesville, Florida, United States, 1992
  • MS in Statistics, University of Florida, Gainesville, Florida, United States, 1988
  • BA in Mathematics, St. Cloud State University, St. Cloud, Minnesota, United States, 1986

Areas of Research Interest

  • Key Phrases: Statistical inference for Categorical Data, Exact and Approximate Interval Estimation, Foundations of Mathematical Statistics and Inference (Freq, Bayes, Fiducial, Fuzzy), Causal inference, Randomization Tests, Missing Data, Generalized Regression Modeling

Selected Awards and Honors

  • Lane Davis Award for Honors Team Teaching, The University of Iowa, 2012
  • Elected Fellow of the American Statistical Association, 2007
  • Distinguished Alumnus Award, University of Florida, Department of Statistics, 2004
  • Collegiate Teaching Award, The University of Iowa, 2003

Selected Publications

  • Lauritsen, J., Heimer, K. & Lang, J. B. (2018). The Enduring Significance of Racial and Ethnic Disparities in Male Violent Victimization: An Analysis of National Crime Survey Victimization Data, 1973-2010. DuBois Review, 69-87.
  • Lang, J. B. (2018). CI.binom() Supporting software for "Mean-Minimum Exact Confidence Intervals," The American Statistician (Lang, 2017).
  • Lang, J. B. (2017). Mean-Minimum Exact Confidence Intervals. The American Statistician, 71(4), 354-368.
  • Iannario, M., Lang, J. (2016). Improved Tests of Conditional Independence in Stratified Tables. Statistics in Medicine, 35(25), 4573-4587.
  • Lang, J. (2015). A Closer Look at Testing the ‘No-Treatment-Effect’ Hypothesis in Comparative Experiments. Statistical Science, 30(3), 352-371. DOI: 10.1214/15-sts513.
  • Lang, J. B. (2008). Score and Profile Likelihood Confidence Intervals for Contingency Table Parameters. Statistics in Medicine, 5975-5990.
  • Lang, J. B. (2005). Homogeneous Linear Predictor Models for Contingency Tables. Journal of the American Statistical Association-Theory and Methods, 121-134.
  • Lang, J. B. (2004). Multinomial-Poisson Homogeneous Models for Contingency Tables. Annals of Statistics, 340-383.
  • Lang, J. B. (1994). Simultaneously Modeling the Joint and Marginal Distributions of Multivariate Categorical Response Data. Journal of the American Statistical Association-Theory and Methods, 625-632.
  • Lang, J., Iannario, M. (2013). Improved Tests of Independence in Singly-Ordered Two-Way Contingency Tables. Computational Statistics and Data Analysis, 68, 339-351. DOI: 10.1016/j.csda.2013.06.014.
Last Modified Date: May 10, 2021