The American Statistician

2012 - 2025

Continuation of The American Statistician.

Current editor(s): Eric Sampson

From Taylor & Francis Journals
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Volume 74, issue 4, 2020

A Time-Series Model for Underdispersed or Overdispersed Counts pp. 317-328

Iain L. MacDonald and Feroz Bhamani

Big Data? Statistical Process Control Can Help! pp. 329-344

Peihua Qiu

Applications of the Fractional-Random-Weight Bootstrap pp. 345-358

Li Xu, Chris Gotwalt, Yili Hong, Caleb B. King and William Q. Meeker

Assessing Bayes Factor Surfaces Using Interactive Visualization and Computer Surrogate Modeling pp. 359-369

Christopher T. Franck and Robert B. Gramacy

Decision-Theoretic Hypothesis Testing: A Primer With R Package OptSig pp. 370-379

Jae Kim

Going Viral, Binge-Watching, and Attention Cannibalism pp. 380-391

Scott D. Grimshaw, Natalie J. Blades and Candace Berrett

Random Forest Prediction Intervals pp. 392-406

Haozhe Zhang, Joshua Zimmerman, Dan Nettleton and Daniel J. Nordman

Gaussian Mixture Representation of the Laplace Distribution Revisited: Bibliographical Connections and Extensions pp. 407-412

Tomasz J. Kozubowski and Krzysztof Podgórski

Revisiting Jeffreys’ Example: Bayes Test of the Normal Mean pp. 413-415

Malay Ghosh

Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach pp. 416-417

Wen Li and Thomas O. Jemielita

Multiple Imputation in Practice: With Examples Using IVEware pp. 417-417

Qixuan Chen

Xinjie Hu, Aekyung Jung, and Gengsheng Qin (2020), “Interval Estimation for the Correlation Coefficient,” The American Statistician, 74:1, 29–36: Comment by Krishnamoorthy and Xia pp. 418-418

Kalimuthu Krishnamoorthy and Yanping Xia

A Response to the Letter to the Editor on “Interval Estimation for the Correlation Coefficient,” The American Statistician, 74:1, 29–36: Comment by Krishnamoorthy and Xia pp. 419-419

Xinjie Hu, Aekyung Jung and Gengsheng Qin

Editorial Collaborators pp. 420-421

The Editors

Volume 74, issue 3, 2020

The Detection of Nonnegligible Directional Effects With Associated Measures of Statistical Significance pp. 213-217

Melinda H. McCann and Joshua D. Habiger

Some Improvements on Markov's Theorem with Extensions pp. 218-225

Haruhiko Ogasawara

Compound Regression and Constrained Regression: Nonparametric Regression Frameworks for EIV Models pp. 226-232

Ling Leng and Wei Zhu

Nonparametric Estimation of the Conditional Distribution at Regression Boundary Points pp. 233-242

Srinjoy Das and Dimitris N. Politis

On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value pp. 243-248

Sander Greenland, Michael P. Fay, Erica H. Brittain, Joanna H. Shih, Dean A. Follmann, Erin E. Gabriel and James M. Robins

Bayesian Causality pp. 249-257

Pierre Baldi and Babak Shahbaba

Detecting Directionality in Time Series pp. 258-266

Mahayaudin M. Mansor, David A. Green and Andrew V. Metcalfe

Bias in Small-Sample Inference With Count-Data Models pp. 267-273

McKinley L. Blackburn

A New Analysis Strategy for Designs With Complex Aliasing pp. 274-281

Andrew Kane and Abhyuday Mandal

Trend and Return Level of Extreme Snow Events in New York City pp. 282-293

Mintaek Lee and Jaechoul Lee

On a Proper Bayes, but Inadmissible Estimator pp. 294-296

Pankaj Bhagwat and Éric Marchand

On the Maximum–Minimums Identity: Extension and Applications pp. 297-300

Ibrahim Salama and Gary Koch

Was Quetelet’s Average Man Normal? pp. 301-306

Eugene D. Gallagher

The 9 Pitfalls of Data Science pp. 307-307

Yongdai Kim

Feature Engineering and Selection: A Practical Approach for Predictive Models pp. 308-309

Brandon Butcher and Brian J. Smith

Modern Statistics for Modern Biology pp. 309-311

Bailey K. Fosdick and G. Brooke Anderson

Surprises in Probability: Seventeen Short Stories pp. 311-311

Jonathan M. Wells

Time Series: A Data Analysis Approach Using R pp. 312-312

Robert B. Lund

Comment on “Test for Trend With a Multinomial Outcome” by Szabo (2019) pp. 313-314

Ronald Christensen

Micha Mandel (2020), “The Scaled Uniform Model Revisited,” The American Statistician, 74:1, 98–100: Comment pp. 315-315

Gunnar Taraldsen

Volume 74, issue 2, 2020

Where Should I Publish My Sports Paper? pp. 103-108

Tim B. Swartz

Wilson Confidence Intervals for Binomial Proportions With Multiple Imputation for Missing Data pp. 109-115

Anne Lott and Jerome P. Reiter

The Relative Performance Index: Neutralizing Simpson's Paradox pp. 116-124

Ernest C. Davenport,, Kyle Nickodem, Mark L. Davison, Gareth Phillips and Edmund Graham

Iterative Multiple Imputation: A Framework to Determine the Number of Imputed Datasets pp. 125-136

Vahid Nassiri, Geert Molenberghs, Geert Verbeke and João Barbosa-Breda

Informed Bayesian t-Tests pp. 137-143

Quentin F. Gronau, Alexander Ly and Eric-Jan Wagenmakers

Visualizing Tests for Equality of Covariance Matrices pp. 144-155

Michael Friendly and Matthew Sigal

Plotting Likelihood-Ratio-Based Confidence Regions for Two-Parameter Univariate Probability Models pp. 156-168

Christopher Weld, Andrew Loh and Lawrence Leemis

Archetypal Analysis With Missing Data: See All Samples by Looking at a Few Based on Extreme Profiles pp. 169-183

Irene Epifanio, M. Victoria Ibáñez and Amelia Simó

Time Parameterizations in Cluster Randomized Trial Planning pp. 184-189

Kelsey L. Grantham, Andrew B. Forbes, Stephane Heritier and Jessica Kasza

How Does a Statistician Raise an Army? The Time When John W. Tukey, a Team of Luminaries, and a Statistics Graduate Student Repaired the Vietnam Selective Service Lotteries pp. 190-196

Tim Johnson, Christopher T. Dawes and Dalton Conley

Lest We Forget: U.S. Selective Service Lotteries, 1917–2019 pp. 197-206

James A. Hanley

Capture-Recapture Methods for the Social and Medical Sciences pp. 207-208

Daniel Manrique-Vallier

The Art of Statistics: How to Learn From Data pp. 207-207

Jong Hee Park

Model-Based Clustering and Classification for Data Science: With Applications in R pp. 208-209

Seung Jun Shin

R Markdown: The Definitive Guide pp. 209-210

Paul Johnson

Did Phlegon Actually Use a Stem-and-Leaf Display? pp. 211-211

David C. Hoaglin

Correction pp. 212-212

The Editors

Volume 74, issue 1, 2020

The Democratization of Data Science Education pp. 1-7

Sean Kross, Roger D. Peng, Brian S. Caffo, Ira Gooding and Jeffrey T. Leek

Fostering Undergraduate Data Science pp. 8-16

Fulya Gokalp Yavuz and Mark Daniel Ward

A Short Note on Almost Sure Convergence of Bayes Factors in the General Set-Up pp. 17-20

Debashis Chatterjee, Trisha Maitra and Sourabh Bhattacharya

Generating Correlation Matrices With Specified Eigenvalues Using the Method of Alternating Projections pp. 21-28

Niels G. Waller

Interval Estimation for the Correlation Coefficient pp. 29-36

Xinjie Hu, Aekyung Jung and Gengsheng Qin

The Johnson System of Frequency Curves—Historical, Graphical, and Limiting Perspectives pp. 37-52

Johan René van Dorp and M. C. Jones

A Note on Item Response Theory Modeling for Online Customer Ratings pp. 53-63

Chien-Lang Su, Sun-Hao Chang and Ruby Chiu-Hsing Weng

On the Loss Robustness of Least-Square Estimators pp. 64-67

Tamal Ghosh, Malay Ghosh and Tatsuya Kubokawa

Comment on “A Note on Collinearity Diagnostics and Centering” by Velilla (2018) pp. 68-71

Román Salmerón Gómez, Catalina García García and Jose García Pérez

Models for Geostatistical Binary Data: Properties and Connections pp. 72-79

Victor De Oliveira

Two-Tailed p-Values and Coherent Measures of Evidence pp. 80-86

Peter H. Peskun

A Shiny Update to an Old Experiment Game pp. 87-92

Robert B. Gramacy

Further Examples Related to the Identical Distribution of X/(X+Y) and Y/(X+Y) pp. 93-97

Barry C. Arnold

The Scaled Uniform Model Revisited pp. 98-100

Micha Mandel

Benjamin, D. J., and Berger, J. O. (2019), “Three Recommendations for Improving the Use of p-Values”, The American Statistician, 73, 186–191: Comment by Foulley pp. 101-102

Jean-Louis Foulley