Simultaneous Statistical Inference

Rupert G. Jr. Miller

ISBN 10: 146138124X / ISBN 13: 9781461381242

Editore: Springer New York, 2011

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Simultaneous Statistical Inference, which was published originally in 1966 by McGraw-Hill Book Company, went out of print in 1973. Since then, it has been available from University Microfilms International in xerox form. With this new edition Springer-Verla. Codice articolo 4196190

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Titolo: Simultaneous Statistical Inference

Casa editrice: Springer New York

Data di pubblicazione: 2011

Legatura: Brossura

Condizione: New

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Riassunto:

Simultaneous Statistical Inference, which was published originally in 1966 by McGraw-Hill Book Company, went out of print in 1973. Since then, it has been available from University Microfilms International in xerox form. With this new edition Springer-Verlag has republished the original edition along with my review article on multiple comparisons from the December 1977 issue of the Journal of the American Statistical Association. This review article covered developments in the field from 1966 through 1976. A few minor typographical errors in the original edition have been corrected in this new edition. A new table of critical points for the studentized maximum modulus is included in this second edition as an addendum. The original edition included the table by K. C. S. Pillai and K. V. Ramachandran, which was meager but the best available at the time. This edition contains the table published in Biometrika in 1971 by G. 1. Hahn and R. W. Hendrickson, which is far more comprehensive and therefore more useful. The typing was ably handled by Wanda Edminster for the review article and Karola Decleve for the changes for the second edition. My wife, Barbara, again cheerfully assisted in the proofreading. Fred Leone kindly granted permission from the American Statistical Association to reproduce my review article. Also, Gerald Hahn, Richard Hendrickson, and, for Biometrika, David Cox graciously granted permission to reproduce the new table of the studentized maximum modulus. The work in preparing the review article was partially supported by NIH Grant ROI GM21215.

Contenuti:

1 Introduction.- 1 Case of two means.- 2 Error rates.- 2.1 Probability of a nonzero family error rate.- 2.2 Expected family error rate.- 2.3 Allocation of error.- 3 Basic techniques.- 3.1 Repeated normal statistics.- 3.2 Maximum modulus (Tukey).- 3.3 Bonferroni normal statistics.- 3.4 ?2 projections (Scheffé).- 3.5 Allocation.- 3.6 Multiple modulus tests (Duncan).- 3.7 Least significant difference test (Fisher).- 4 p-mean significance levels.- 5 Families.- 2 Normal Univariate Techniques.- 1 Studentized range (Tukey).- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 F projections (Scheffé)48.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 Bonferroni t statistics.- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 Studentized maximum modulus.- 4.1 Method.- 4.2 Applications.- 4.3 Comparison.- 4.4 Derivation.- 4.5 Distributions and tables.- 5 Many-one t statistics76.- 5.1 Method.- 5.2 Applications.- 5.3 Comparison.- 5.4 Derivation.- 5.5 Distributions and tables.- 6 Multiple range tests (Duncan).- 6.1 Method.- 6.2 Applications.- 6.3 Comparison.- 6.4 Derivation.- 6.5 Distributions and tables.- 7 Least significant difference test (Fisher).- 7.1 Method.- 7.2 Applications.- 7.3 Comparison.- 7.4 Derivation.- 7.5 Distributions and tables.- 8 Other techniques.- 8.1 Tukey’s gap-straggler-variance test.- 8.2 Shortcut methods.- 8.3 Multiple F tests.- 8.4 Two-sample confidence intervals of predetermined length.- 8.5 An improved Bonferroni inequality.- 9 Power.- 10 Robustness.- 3 Regression Techniques.- 1 Regression surface confidence bands.- 1.1 Method.- 1.2 Comparison.- 1.3 Derivation.- 2 Prediction.- 2.1 Method.- 2.2 Comparison.- 2.3 Derivation.- 3 Discrimination.- 3.1 Method.- 3.2 Comparison.- 3.3 Derivation.- 4 Other techniques.- 4.1 Linear confidence bands.- 4.2 Tolerance intervals.- 4.3 Unlimited discrimination intervals.- 4 Nonparametric Techniques.- 1 Many-one sign statistics (Steel).- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 k-sample sign statistics.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 Many-one rank statistics (Steel).- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 k-sample rank statistics.- 4.1 Method.- 4.2 Applications.- 4.3 Comparison.- 4.4 Derivation.- 4.5 Distributions and tables.- 5 Signed-rank statistics.- 6 Kruskal-Wallis rank statistics (Nemenyi).- 6.1 Method.- 6.2 Applications.- 6.3 Comparison.- 6.4 Derivation.- 6.5 Distributions and tables.- 7 Friedman rank statistics (Nemenyi).- 7.1 Method.- 7.2 Applications.- 7.3 Comparison.- 7.4 Derivation.- 7.5 Distributions and tables.- 8 Other techniques.- 8.1 Permutation tests.- 8.2 Median tests (Nemenyi).- 8.3 Kolmogorov-Smirnov statistics.- 5 Multivariate Techniques.- 1 Single population; covariance scalar unknown.- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 Single population; covariance matrix unknown.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 k populations; covariance matrix unknown.- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 Other techniques.- 4.1 Variances known; covariances unknown.- 4.2 Variance-covariance intervals.- 4.3 Two-sample confidence intervals of predetermined length.- 6 Miscellaneous Techniques.- 1 Outlier detection.- 2 Multinomial populations.- 2.1 Single population.- 2.2 Several populations.- 2.3 Cross-product ratios.- 2.4 Logistic response curves.- 3 Equality of variances.- 4 Periodogram analysis.- 5 Alternative approaches: selection, ranking, slippage.- A Strong Law For The Expected Error Rate.- B TABLES.- I Percentage points of the studentized range.- II Percentage points of the Bonferroni t statistic.- III Percentage points of the studentized maximum modulus.- IV Percentage points of the many-one t statistics.- V Percentage points of the Duncan multiple range test.- VI Percentage points of the many-one sign statistics.- VIII Percentage points of the many-one rank statistics.- IX Percentage points of the k-sample rank statistics.- Developments in Multiple Comparisons 1966–1976.- 1 Introduction.- 2 Papers of special interest.- 2.1 Probability inequalities.- 2.2 Methods for unbalanced ANOVA.- 2.3 Conditional confidence levels.- 2.4 Empirical Bayes approach.- 2.5 Confidence bands in regression.- 3 References.- 4 Bibliography 1966–1976.- 4.1 Survey articles.- 4.2 Probability inequalities.- 4.3 Tables.- 4.4 Normal multifactor methods.- 4.5 Regression.- 4.6 Categorical data.- 4.7 Nonparametric techniques.- 4.8 Multivariate methods.- 4.9 Miscellaneous.- 4.10 Pre-1966 articles missed in [6].- 4.11 Late additions.- 5 List of journals scanned.- Addendum New Table of the Studentized Maximum Modulus.- Table IIIA Percentage points of the studentized maximum modulus.- Author Index.