Sample size determination for step-down multiple test procedures: Orthogonal contrasts and comparisons with a control

DOI10.1016/0378-3758(91)90042-DzbMath0729.62062OpenAlexW2083007877MaRDI QIDQ806865

Anthony J. Hayter, Ajit C. Tamhane

Publication date: 1991

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(91)90042-d

zbMATH Keywords

powernormal distributioncomparisons with a controlsample size determinationoptimum allocationmultivariate t-distributionnonhierarchical familiesorthogonal contrastssingle-step proceduresstep-down multiple comparison procedures

Mathematics Subject Classification ID

Design of statistical experiments (62K99) Paired and multiple comparisons; multiple testing (62J15) Probabilistic methods, stochastic differential equations (65C99)

Related Items (11)

A more powerful step-up procedure for controlling the false discovery rate under independence ⋮ Multiple Comparisons Controlling Expected Number of False Discoveries ⋮ Multiple comparison procedures for finding non-maximum normal means ⋮ Optimal design for \(p\)-value consistent step-up procedures for multiple comparisons with a control in direction-mixed families ⋮ Optimal Multiple Testing and Design in Clinical Trials ⋮ Unnamed Item ⋮ Step-Up Procedure for Multiple Comparison with a Control for Multivariate Normal Means ⋮ Multiple comparison procedures for optimally discriminating between good, equivalent, and bad treatments with respect to a control ⋮ A modified Dunnett and Tamhane step-up approach for establishing superiority/equivalence of a new treatment compared with \(k\) standard treatments ⋮ Sample size determination in step-down and step-up multiple tests for comparing treatments with a control ⋮ A method of power assessment for tests comparing several treatments with a control

Cites Work

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• Control of directional errors with stagewise multiple test procedures
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• Some selection rules for comparing p processes with a standard
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• THE DISTRIBUTION OF RANGE IN SAMPLES FROM A NORMAL POPULATION, EXPRESSED IN TERMS OF AN INDEPENDENT ESTIMATE OF STANDARD DEVIATION
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