The American Statistician
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Publication Venue For
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Multiple Imputation Inference with Integer-Valued Point Estimates.
76:323-328.
2022
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Statistical Challenges in Agent-Based Modeling.
75:235-242.
2021
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Wilson Confidence Intervals for Binomial Proportions With Multiple Imputation for Missing Data.
74:109-115.
2020
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Disease Mapping With Generative Models.
73:213-223.
2019
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The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making.
73:56-68.
2019
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Three Recommendations for Improving the Use of p-Values.
73:186-191.
2019
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Infrastructure and Tools for Teaching Computing Throughout the Statistical Curriculum.
72:58-65.
2018
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Facilitating the Calculation of the Efficient Score Using Symbolic Computing..
72:199-205.
2018
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An Empirical Comparison of Multiple Imputation Methods for Categorical Data.
71:162-170.
2017
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Has It Really Been Demonstrated That Most Genomic Research Findings Are False?.
69:1-4.
2015
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Are independent parameter draws necessary for multiple imputation?.
67:143-149.
2013
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Applications of multiple systems estimation in human rights research.
67:191-200.
2013
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Rejoinder.
67:205-206.
2013
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Efficient Classification-Based Relabeling in Mixture Models..
65:16-20.
2011
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Construction of confidence intervals and regions for ordered binomial probabilities.
64:291-298.
2010
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A note on Bayesian inference after multiple imputation.
64:159-163.
2010
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Non-linear Models for Longitudinal Data..
63:378-388.
2009
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Flexible Frames and Control Sampling in Case-Control Studies: Weighters (Survey Statisticians) Versus Anti-Weighters (Epidemiologists)..
62:307-313.
2008
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A framework for evaluating the utility of data altered to protect confidentiality.
60:224-232.
2006
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Discussion of “statistical research: Some advice for beginners” by M. Hamada and R. Sitter.
58:197-198.
2004
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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
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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
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The role of informative priors in zero-numerator problems: Being conservative versus being candid.
56:1-4.
2002
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Calibration of p values for testing precise null hypotheses.
55:62-71.
2001
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A comparison of approximate interval estimators for the Bernoulli parameter.
50:388-389.
1996
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Simple counterexamples against the conditionality principle - Comment.
50:382-383.
1996
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A Comparison of Approximate Interval Estimators for the Bernoulli Parameter.
50:63-68.
1996
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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
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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
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Integrating scientific writing into a statistics curriculum: A course in statistically based scientific writing.
48:117-119.
1994
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THE FATE WORSE THAN DEATH AND OTHER CURIOSITIES AND STUPIDITIES - COMMENT.
44:187-188.
1990
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Heterogeneity's ruses: some surprising effects of selection on population dynamics..
39:176-185.
1985
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DISFIT: A Program for Fitting Discrete Distributions to Data.
35:260-260.
1981
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DISFIT: A program for fitting discrete distributions to data.
35:260.
1981
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Comment.
32:54-56.
1978