000			03251nam a22005057a 4500
001			sulb-eb0021981
003			BD-SySUS
005			20160413122215.0
007			cr nn 008mamaa
008			120904s2013 xxu| s |||| 0|eng d
020			_a9781461443223 _9978-1-4614-4322-3
024	7		_a10.1007/978-1-4614-4322-3 _2doi
050		4	_aRC261-271
072		7	_aMJCL _2bicssc
072		7	_aMED062000 _2bisacsh
082	0	4	_a614.5999 _223
245	1	0	_aModern Clinical Trial Analysis _h[electronic resource] / _cedited by Wan Tang, Xin Tu.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aX, 254 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aApplied Bioinformatics and Biostatistics in Cancer Research
505	0		_aPreface -- Survival Analysis -- Longitudinal Data Analysis -- Assessment of Diagnostic Tests and Instruments -- Analysis of Sequential Clinical Trials -- Dynamic Treatment Regimes -- Statistical Issues with Trial Data and Economic Modeling for Cost-effectiveness Evaluation -- Active-controlled Clinical Trials -- Thorough QT/QTc Clinical Trials -- Causal Inference in Cancer Clinical Trials -- Index.
520			_aThis volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. Starting with survival data analysis, this book transitions from such a classic topic to modern issues by stepping through diagnostic test and instrument assessment, sequential and dynamic treatment regimen, cost-effectiveness evaluation, equivalence testing.  As some type of cancer such as the effect of smoking on lung cancer cannot be studied using randomized trials, a chapter on analysis of non-randomized studies is also included.  The book concludes with a chapter discussing the opportunities and challenges that lie ahead in developing on person-centered treatment regimens.  The book provides an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out the analyses. Medical researchers with some background in clinical trial design and regression analysis as well as biostatisticians will find this book informative and helpful.   .
650		0	_aMedicine.
650		0	_aCancer research.
650		0	_aOncology.
650		0	_aBioinformatics.
650	1	4	_aBiomedicine.
650	2	4	_aCancer Research.
650	2	4	_aOncology.
650	2	4	_aBioinformatics.
700	1		_aTang, Wan. _eeditor.
700	1		_aTu, Xin. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461443216
830		0	_aApplied Bioinformatics and Biostatistics in Cancer Research
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-4322-3
912			_aZDB-2-SBL
942			_2Dewey Decimal Classification _ceBooks
999			_c44073 _d44073