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Statistical Methods for Dynamic Treatment Regimes (Record no. 23270)

000 -LEADER
fixed length control field 03770nam a22004335i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151450.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130722s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461474289
978-1-4614-7428-9
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
264 #1 -
-- New York, NY :
-- Springer New York :
-- Imprint: Springer,
-- 2013.
912 ## -
-- ZDB-2-SMA
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chakraborty, Bibhas.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Statistical Methods for Dynamic Treatment Regimes
Medium [electronic resource] :
Remainder of title Reinforcement Learning, Causal Inference, and Personalized Medicine /
Statement of responsibility, etc by Bibhas Chakraborty, Erica E.M. Moodie.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 204 p. 22 illus., 5 illus. in color.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Statistics for Biology and Health,
International Standard Serial Number 1431-8776
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- The Data: Observational Studies and Sequentially Randomized Trials -- Statistical Reinforcement Learning -- Estimation of Optimal DTRs by Modeling Contrasts of Conditional Mean Outcomes -- Estimation of Optimal DTRs by Directly Modeling Regimes -- G-computation: Parametric Estimation of Optimal DTRs -- Estimation DTRs for Alternative Outcome Types -- Inference and Non-regularity -- Additional Considerations and Final Thoughts -- Glossary -- Index -- References.
520 ## - SUMMARY, ETC.
Summary, etc Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Medical records
General subdivision Data processing.
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistics for Life Sciences, Medicine, Health Sciences.
Topical term or geographic name as entry element Statistics, general.
Topical term or geographic name as entry element Health Informatics.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Moodie, Erica E.M.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781461474272
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-7428-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-10AUM Main Library2014-04-10 2014-04-10 E-Book   AUM Main Library519.5

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