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008			150903s2006 xxu| o |||| 0|eng d
020			_a9780387449708 _99780387449708
024	7		_a10.1007/9780387449708 _2doi
035			_avtls000331457
039		9	_a201509030731 _bVLOAD _c201404121844 _dVLOAD _c201404091612 _dVLOAD _c201401311416 _dstaff _y201401301210 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aProschan, Michael A. _eautor _9304871
245	1	0	_aStatistical Monitoring of Clinical Trials : _bA Unified Approach / _cby Michael A. Proschan, K. K. Gordan Lan, Janet Turk Wittes.
264		1	_aNew York, NY : _bSpringer New York, _c2006.
300			_axiii, 258 páginas, 32 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aStatistics for Biology and Health, _x1431-8776
500			_aSpringer eBooks
505	0		_aA General Framework -- Power: Conditional, Unconditional, and Predictive -- Historical Monitoring Boundaries -- Spending Functions -- Practical Survival Monitoring -- Inference Following a Group-Sequential Trial -- Options When Brownian Motion Does Not Hold -- Monitoring for Safety -- Bayesian Monitoring -- Adaptive Sample Size Methods -- Topics Not Covered -- Appendix I: The Logrank and Related Tests -- Appendix II: Group-Sequential Software.
520			_aThe approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion (``the B-value") irrespective of the test statistic. The so-called B-value approach to monitoring allows us to use, for different types of trials, the same boundaries and the same simple formula for computing conditional power. Although Brownian motion may sound complicated, the authors make the approach easy by starting with a simple example and building on it, one piece at a time, ultimately showing that Brownian motion works for many different types of clinical trials. The book will be very valuable to statisticians involved in clinical trials. The main body of the chapters is accessible to anyone with knowledge of a standard mathematical statistics text. More mathematically advanced readers will find rigorous developments in appendices at the end of chapters. Reading the book will develop insight into not only monitoring, but power, survival analysis, safety, and other statistical issues germane to clinical trials. Michael Proschan, Gordon Lan, and Janet Wittes are elected Fellows of the American Statistical Association. All have spent formative years in the Biostatistics Research Branch of the National Heart, Lung, and Blood Institute (NHLBI/NIH). While there, they were intimately involved in the design and statistical monitoring of large-scale randomized clinical trials, developing methodology to aid in their monitoring. For example, Lan developed, with DeMets, the now widely-used spending function approach to group sequential designs, whose properties were further investigated by Proschan. The B-value approach used in the book was introduced in a very influential paper by Lan and Wittes. The statistical theory behind conditional power was developed by Lan, along with Simon and Halperin, and was the cornerstone for the conditional error approach to adaptive clinical trials introduced by Proschan and Hunsberger. All three authors have expertise in adaptive methodology for clinical trials. Michael Proschan is a Mathematical Statistician at the National Institutes of Health; Gordon Lan is Senior Director of Biometrics at Johnson & Johnson Pharmaceutical Research & Development, L.L.C.; Janet Wittes is President of Statistics Collaborative, a statistical consulting company she founded in 1990.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aLan, K. K. Gordan. _eautor _9304872
700	1		_aWittes, Janet Turk. _eautor _9304873
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387300597
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-44970-8 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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