Multiple comparison procedures
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Multiple comparison procedures a selected bibliography by Wayne W. Daniel

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Published by Vance Bibliographies in Monticello, Ill .
Written in English

Subjects:

  • Multiple comparisons (Statistics) -- Bibliography.

Book details:

Edition Notes

Cover title.

StatementWayne W. Daniel.
SeriesPublic administration series : Bibliography ;, P-514, Public administration series--bibliography ;, P-514.
Classifications
LC ClassificationsZ6654.M78 D36, QA278.4 D36
The Physical Object
Pagination36 p. ;
Number of Pages36
ID Numbers
Open LibraryOL4147553M
LC Control Number80126810

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User Review - Flag as inappropriate I found this to be a useful book. It is fairly easy to read and understand. It goes through most of the multiple comparison procedures that one might want and describes how to use them and their limitations. It helps me to have multiple sources, in part because not every statisticial agrees with all the others.4/5(1). Book Series: Wiley Series in Probability and Statistics About this Book Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. Yosef Hochberg, Ph.D., professor in the School of Mathematical Sciences at Tel Aviv University, has taught several courses in multiple comparisons. He has published an impressive number of articles and technical reports on various statistical methods and is an author (with Ajit Tamhane) of Multiple Comparison Procedures. Get this from a library! Multiple comparison procedures. [Yosef Hochberg; Ajit C Tamhane] -- Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in .

Multiple comparison procedures Comparison of MCPS Violations of assumptions and robustness Multiple comparisons for the two-way ANOVA: factorial or randomized blocks. Series Title: Quantitative applications in the social sciences, no. Responsibility: Larry E. Toothaker. More information: Table of contents; Publisher. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. The fact that we have presented five different multiple-comparison procedures makes it obvious that there is no universally best procedure for making post hoc comparisons. In fact, Kirk () points out that there are more than 30 multiple-comparison procedures currently used by researchers. As a result of this, most computer programs offer a. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice by:

Multiple Comparison Procedures. Search form. Buy in print. Menu. Opener. Search form. icon-arrow-top icon-arrow-top. Book; Site; Advanced. Not Found. Opener. Sections. Little Green Book. Multiple Comparison Procedures. Little Green Book. Back to Top. Methods Map. Critical value. Explore the Methods Map. Related Content. Multiple Comparisons. Multiple Comparisons for the Two-Way ANOVA: Factorial or Randomized Blocks When the topic of multiple comparisons is covered in most statistics or experimental design texts, considerable attention is placed upon MCPs for a one-way ANOVA, that is, a completely randomized design. 1. Two Early Multiple Comparison Procedures 2. 2. Basic Notions and Philosophy of Multiple Comparisons 5. 3. Examples Part I. Procedures Based in Classical Approaches for Fixed-Effects Linear Models with Normal Homoscedastic Independent Errors 2. Some Theory of Multiple Comparison Procedures for Fixed-Effects Linear Models 2. In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. In certain fields it is known as the look-elsewhere effect.. The more inferences are made, the more likely erroneous inferences are to occur.