000			03251cam a2200289 a 4500
008			120511s2010 dcua b 000 0 eng c
020			_a9780309158145
020			_a0309158141
040			_aSDU
050	0	0	_aR853 _bN277 P 2010
110	2		_aNational Research Council (U.S.).
245	1	4	_aThe prevention and treatment of missing data in clinical trials / _cPanel on Handling Missing Data in Clinical Trials, Committee on National Statistics, Division of Behavioral and Social Sciences, National Research Council of the National Academies.
260			_aWashington, D.C. : _bNational Academies Press, _c2010.
300			_a144 p. : _bill.
505	0		_aIntroduction and background -- Trial designs to reduce the frequency of missing data -- Trial strategies to reduce the frequency of missing data -- Drawing inferences from incomplete data -- Principles and methods of sensitivity analyses -- Conclusions and recommendations.
505	0		_aHKBU library
518			_aYT2025 M09
520			_a"Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data."--Publisher's description.
650		0	_aClinical trials _xStatistical methods. _9194133
650		0	_aExperimental design.
650	1	2	_aRandomized Controlled Trials as Topic _xstatistics & numerical data. _9204602
650	2	2	_aBiomedical Research _xstandards. _9204603
710	2		_aNational Research Council (U.S.). _bCommittee on National Statistics.
710	2		_aNational Academies Press (U.S.) _9187834
900			_a33314 = C.1 ศูนย์วิทยาศาสตร์
942			_cGBE _2lcc
999			_c107215 _d107215