The American Statistician

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  Publication Venue For

  • Multiple Imputation Inference with Integer-Valued Point Estimates 2022
  • Statistical Challenges in Agent-Based Modeling.  75:235-242. 2021
  • Wilson Confidence Intervals for Binomial Proportions With Multiple Imputation for Missing Data.  74:109-115. 2020
  • Disease Mapping With Generative Models.  73:213-223. 2019
  • The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making.  73:56-68. 2019
  • Three Recommendations for Improving the Use of p-Values.  73:186-191. 2019
  • Infrastructure and Tools for Teaching Computing Throughout the Statistical Curriculum.  72:58-65. 2018
  • Facilitating the Calculation of the Efficient Score Using Symbolic Computing..  72:199-205. 2018
  • An Empirical Comparison of Multiple Imputation Methods for Categorical Data.  71:162-170. 2017
  • Has It Really Been Demonstrated That Most Genomic Research Findings Are False?.  69:1-4. 2015
  • Are independent parameter draws necessary for multiple imputation?.  67:143-149. 2013
  • Applications of multiple systems estimation in human rights research.  67:191-200. 2013
  • Rejoinder.  67:205-206. 2013
  • Efficient Classification-Based Relabeling in Mixture Models..  65:16-20. 2011
  • Construction of confidence intervals and regions for ordered binomial probabilities.  64:291-298. 2010
  • A note on Bayesian inference after multiple imputation.  64:159-163. 2010
  • Non-linear Models for Longitudinal Data..  63:378-388. 2009
  • Flexible Frames and Control Sampling in Case-Control Studies: Weighters (Survey Statisticians) Versus Anti-Weighters (Epidemiologists)..  62:307-313. 2008
  • A framework for evaluating the utility of data altered to protect confidentiality.  60:224-232. 2006
  • Discussion of “statistical research: Some advice for beginners” by M. Hamada and R. Sitter.  58:197-198. 2004
  • Hitchcock, d. b. (2003), “a history of the metropolis-hastings algorithm,” the american statistician, 57, 254-257: Comment by kotz, johnson, read, and banks and reply.  58:90. 2004
  • Winkler, R. L., Smith, J. E., and Fryback, D. G. (2002), "The role of informative priors in zero-numerator problems: Being conservative versus being candid," the american statistician, 56, 1-4: Comments by browne [1] (multiple letters).  56:252-253. 2002
  • The role of informative priors in zero-numerator problems: Being conservative versus being candid.  56:1-4. 2002
  • Calibration of p values for testing precise null hypotheses.  55:62-71. 2001
  • A comparison of approximate interval estimators for the Bernoulli parameter.  50:388-389. 1996
  • Simple counterexamples against the conditionality principle - Comment.  50:382-383. 1996
  • A Comparison of Approximate Interval Estimators for the Bernoulli Parameter.  50:63-68. 1996
  • Helland, Inge S. (1995), “Simple counterexamples against the conditionality principle,” the American statistician, 49, 351-356 comment by berger and reply.  50:382-384. 1996
  • Leemis, Lawrence M., and Trivedi, Kishor S. (1996), “A comparison of approximate interval estimators for the bernoulli parameter,” the American statistician, 50, 63-68: Comment by klotz and reply.  50:388-389. 1996
  • Integrating scientific writing into a statistics curriculum: A course in statistically based scientific writing.  48:117-119. 1994
  • THE FATE WORSE THAN DEATH AND OTHER CURIOSITIES AND STUPIDITIES - COMMENT.  44:187-188. 1990
  • Heterogeneity's ruses: some surprising effects of selection on population dynamics..  39:176-185. 1985
  • DISFIT: A Program for Fitting Discrete Distributions to Data.  35:260-260. 1981
  • DISFIT: A program for fitting discrete distributions to data.  35:260. 1981
  • Comment.  32:54-56. 1978