Informative hypotheses (Record no. 11840)

MARC details
000 -LEADER
fixed length control field 04333cam a2200373Ia 4500
001 - CONTROL NUMBER
control field CAH0KE13934PDF
003 - CONTROL NUMBER IDENTIFIER
control field BD-DhSAU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20151012144306.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 120329s2012 flua sb 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781439880524 (ebook : PDF)
040 ## - CATALOGING SOURCE
Original cataloging agency BD-DhSAU
Transcribing agency BD-DhSAU
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (OCLC)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) BF39
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) .H625 2012
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC)
Classification number 300.727
Item number H719
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Hoijtink, Herbert.
245 10 - TITLE STATEMENT
Title Informative hypotheses
Medium [electronic resource] :
Remainder of title theory and practice for behavioral and social scientists /
Statement of responsibility, etc. Herbert Hoijtink.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. Boca Raton :
Name of publisher, distributor, etc. CRC,
Date of publication, distribution, etc. c2012.
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 227 p. :
Other physical details ill.
490 1# - SERIES STATEMENT
Series statement Chapman & Hall/CRC statistics in the social and behavioral sciences series
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (p. 217-224) and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction -- 2. Bayesian evaluation of informative hypotheses -- 3. Other models, other approaches, and software -- 4. Statistical foundations.
520 ## - SUMMARY, ETC.
Summary, etc. "When scientists formulate their theories, expectations, and hypotheses, they often use statements like: "I expect mean A to be bigger than means B and C"; "I expect that the relation between Y and both X1 and X2 is positive"; and "I expect the relation between Y and X1 to be stronger than the relation between Y and X2". Stated otherwise, they formulate their expectations in terms of inequality constraints among the parameters in which they are interested, that is, they formulate Informative Hypotheses.There is currently a sound theoretical foundation for the evaluation of informative hypotheses using Bayes factors, p-values and the generalized order restricted information criterion. Furthermore, software that is often free is available to enable researchers to evaluate the informative hypotheses using their own data. The road is open to challenge the dominance of the null hypothesis for contemporary research in behavioral, social, and other sciences"--
Assigning source Provided by publisher.
520 ## - SUMMARY, ETC.
Summary, etc. "Preface Providing advise to behavioral and social scientists is the most interesting and challenging part of my work as a statistician. It is an opportunity to apply statistics in situations that usually have no resemblance to the clear cut examples discussed in most text books on statistics. A fortiori, it is not unusual that scientists have questions to which I do not have a straightforward answer, either because the question has not yet been considered by statisticians, or, because existing statistical theory can not easily be applied because there is no software with which it can be implemented. An example of the latter are Informative Hypotheses. When I question scientists with respect to their theories, expectations and hypotheses, they often respond with statements like: I expect mean A to be bigger than means B and C"; I expect that the relation between Y and both X1 and X2 is positive"; and I expect the relation between Y and X1 to be stronger than the relation between Y and X2". Stated otherwise, they formulate their expectations in terms of inequality constraints among the parameters in which they are interested, that is, they formulate Informative Hypotheses. In this book the evaluation of informative hypotheses is introduced for behavioral and social scientists. Chapters 1 and 2 introduce the univariate and multivariate normal lin- ear models and the informative hypotheses that can be formulated in the context of these models. An accessible account of Bayesian evaluation of informative hypotheses is provided in Chapters 3 through 7. There is also an account of the non-Bayesian approaches for the evaluation of informative hypotheses for which software with which these approaches can be implemented is available (Chapter 8)"--
Assigning source Provided by publisher.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print edition.
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Psychology
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social sciences
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Hypothesis.
655 #7 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
Source of term lcsh
776 1# - ADDITIONAL PHYSICAL FORM ENTRY
International Standard Book Number 9781439880517 (hardback)
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Statistics in the social and behavioral sciences series.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://marc.crcnetbase.com/isbn/9781439880524">http://marc.crcnetbase.com/isbn/9781439880524</a>
Electronic format type application/PDF

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