David J. Groggel

Miami University

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John H. Skillings

Baker Hughes (United States)

Robert L. Schaefer

Miami University

David McCarthy

Manchester Royal Infirmary

A. John Bailer

Miami University

Jean Dickinson Gibbons

University of Alabama

John I. Marden

University of Illinois Urbana-Champaign

P. V. Rao

Varsha Bioscience and Technology (India)

A. Papoulis

Farmingdale State College

W. J. Conover

Texas Tech University

Dennis D. Wackerly

University of Florida

Cooperative Institutions

Miami University

University of Pennsylvania

University of Florida

International University Of Health And Welfare Atami Hospital

Manchester Royal Infirmary

University of Manchester

University of California, Santa Barbara

University of Hong Kong

VA Boston Healthcare System

Chinese University of Hong Kong

Author Statistics

Papers

Citation

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Research Field

Probability and Statistics

Technometrics (1992)

David J. Groggel

10.1080/00401706.1992.10484939

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Citations (3)

Practical Nonparametric Statistics

Technometrics (2000)

David J. Groggel

10.1080/00401706.2000.10486067

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Citations (47)

Practical Nonparametric Statistics

Technometrics (2000)

David J. Groggel W. J. Conover

Probability Theory. Statistical Inference. Some Tests Based on the Binomial Distribution. Contingency Tables. Some Methods Based on Ranks. Statistics of the Kolmogorov-Smirnov Type. References. Appendix Tables. Answers to Odd-Numbered Exercises. Index.

Contingency table

Statistical Inference

Binomial (polynomial)

Binomial distribution

Statistical theory

10.2307/1271101

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Citations (11,246)

Statistics Explained: Basic Concepts and Methods

Technometrics (1989)

David J. Groggel R. Kapadia G. Andersson

10.2307/3556155

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Citations (0)

A Monte Carlo study of rank tests for block designs

Communications in Statistics - Simulation and Computation (1987)

David J. Groggel

Abstract Tests based on ranks and the F-test are compared for block designs with n observations per block-treatment combination. Com-parisons are made on level of significance and on power. Rank tests examined include the Friedman as well as those using aligned ranks, weighted ranks, and the rank transformation. It is seen that the performance of these tests in relationship to each other depends on sample size, distribution of the random error term, and the severity of the block effects. Keywords: aligned ranksFriedmanrank transformationweighted ranks

Rank (graph theory)

Statistical power

10.1080/03610918708812607

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Citations (25)

Analyzing and Modeling Rank Data

Technometrics (1996)

David J. Groggel John I. Marden

Introduction Looking at data Formal tests of uniformity: summary statistics and distances Comparing several samples Overview of models Some axiomatics Likelihood methods and exponential families Distance-based models Appendix

Rank (graph theory)

10.2307/1271314

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Citations (517)

Career Pitching Statistics and the Probability of Throwing a No-Hitter in MLB: A Case-Control Study

CHANCE (2010)

David McCarthy David J. Groggel A. John Bailer

Probability and statistics

10.1080/09332480.2010.10739820

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Citations (0)

Nonparametric Methods for Quantitative Analysis

Technometrics (1999)

David J. Groggel Jean Dickinson Gibbons

(1999). Nonparametric Methods for Quantitative Analysis. Technometrics: Vol. 41, No. 1, pp. 75-75.

10.2307/1271000

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Citations (19)

Nonparametric Methods for Quantitative Analysis

Technometrics (1999)

David J. Groggel

10.1080/00401706.1999.10485601

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Citations (3)

Nonparametric estimation in one-way random effects models

Communications in Statistics - Simulation and Computation (1988)

David J. Groggel Dennis D. Wackerly P. V. Rao

We present a rank based method for obtaining point and interval estimates of a scale version of the intraclass correlation coefficient in a one-way random effects model. When compared to the method of Arvesen and Schmitz (1970), the new method is not only applicable to a broader class of situations, but also much easier to implement. Results of a simulation study indicate that the new procedure compares favorably with the Arvesen-Schmitz procedure and the classical normal theory procedure especially If the random components have heavy tailed distributions.

Interval estimation

Point estimation

Rank (graph theory)

10.1080/03610918808812702

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Citations (14)