000 | 02657 a2200421 4500 | ||
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001 | 1032082283 | ||
005 | 20250317100357.0 | ||
008 | 250312042021xx eng | ||
020 | _a9781032082288 | ||
037 |
_bTaylor & Francis _cGBP 45.99 _fBB |
||
040 | _a01 | ||
041 | _aeng | ||
072 | 7 |
_aMBGR1 _2thema |
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_aPBT _2thema |
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_aPS _2thema |
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_aTDCW _2thema |
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_aMBGR1 _2bic |
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_aPBT _2bic |
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072 | 7 |
_aMFN _2bic |
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072 | 7 |
_aPS _2bic |
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072 | 7 |
_aTDCW _2bic |
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072 | 7 |
_aMAT029000 _2bisac |
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_aMED000000 _2bisac |
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_aMED016000 _2bisac |
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_aMED071000 _2bisac |
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_aMED107000 _2bisac |
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072 | 7 |
_a610.21 _2bisac |
|
100 | 1 | _aAnastasios A. Tsiatis | |
245 | 1 | 0 |
_aDynamic Treatment Regimes _bStatistical Methods for Precision Medicine |
250 | _a1 | ||
260 |
_bChapman and Hall/CRC _c20210802 |
||
300 | _a618 p | ||
520 | _bDynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a comprehensive introduction to statistical methodology for the evaluation and discovery of dynamic treatment regimes from data. Researchers and graduate students in statistics, data science, and related quantitative disciplines with a background in probability and statistical inference and popular statistical modeling techniques will be prepared for further study of this rapidly evolving field. A dynamic treatment regime is a set of sequential decision rules, each corresponding to a key decision point in a disease or disorder process, where each rule takes as input patient information and returns the treatment option he or she should receive. Thus, a treatment regime formalizes how a clinician synthesizes patient information and selects treatments in practice. Treatment regimes are of obvious relevance to precision medicine, which involves tailoring treatment selection to patient characteristics in an evidence-based way. Of critical importance to precision medicine is estimation of an optimal treatment regime, one that, if used to select treatments for the patient population, would lead to the most beneficial outcome on average. Key methods for estimation of an optimal treatment regime from data are motivated and described in detail. A dedicated companion website presents full accounts of application of the methods using a comprehensive R package developed by the authors. The authors’ website www.dtr-book.com includes updates, corrections, new papers, and links to useful websites. | ||
700 | 1 |
_aMarie Davidian _4A01 |
|
700 | 1 |
_aShannon T. Holloway _4A01 |
|
700 | 1 |
_aEric B. Laber _4A01 |
|
999 |
_c824 _d824 |