000			04698nam a22004215i 4500
001			978-0-387-44970-8
003			DE-He213
005			20250710083959.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387449708 _a99780387449708
024	7		_a10.1007/978-0-387-44970-8 _2doi
082	0	4	_a519.5 _223
100	1		_aProschan, Michael A. _eauthor.
245	1	0	_aStatistical Monitoring of Clinical Trials _h[recurso electrónico] : _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 p. 32 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStatistics for Biology and Health, _x1431-8776
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.
650		0	_aSTATISTICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICS FOR LIFE SCIENCES, MEDICINE, HEALTH SCIENCES.
700	1		_aLan, K. K. Gordan. _eauthor.
700	1		_aWittes, Janet Turk. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387300597
830		0	_aStatistics for Biology and Health, _x1431-8776
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-44970-8 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c57662 _d57662