Cross-over trials in clinical research临床研究交叉试验

书籍目录

Preface to the second editionPreface to the first edition1  Introduction　1.1   The purpose of this chapter　1.2   An example　1.3   Why are cross-over trials performed?　1.4   Whal are the disadvantages of cross-over trials?　1.5   Where are cross-over trials useful?　1.6   What attitude to cross-over trials will be adopted in this book?　1.7   Carry-over　1.8   What may be done about carry-over?　1.9   Other attitudes to be adopted　1.10  Where else can one find out about cross-over trials?2　Some basic considerations concerning estimation in clinical trials　2.1   The purpose of this chapter　2.2   Assumed background knowledge　2.3   Control in clinical trials　2.4   Two purposes of estimation　2.5   Some features of estimation　2.6   Practical consequences for cross-over trials3  The AB/BA design with Normal data　3.1   An example　3.2   A simple analysis ignoring the effect of period　3.3   Student's approach　3.4   Assumptions in the matched-pairs t approach　3.5   Adjusting for a period effect: two-sample t approach　3.6   Adjusting for a period effect: the Hills-Armitage approach　3.7   Examining period effects　3.8   Testing for carry-over and/or treatment by period interaction　3.9   A model for the AB/BA cross-over　3.10  Carry-over or treatment by period interaction?　3.11  Confidence intervals for carry-over　3.12  Are unbiased estimators of the treatment effect available?　3.13  Can we adjust for carw-over　3.14  The two-stage analysis　3.15  Correcting the two-stage procedure　3.16  Use of baseline measurements　3.17  A Bayesian approach　3.18  Computer analysis　3.19  Further reading　3.20  Recommendations　Appendix 3.1  Analysis with GenStat 　Appendix 3.2  Analysis with S-Plus4  Other outcomes and the AB/BA design　4.1   Introduction　4.2   Transformations　4.3   Non-parametric methods　4.4   Binary outcomes　4.5   Ordered categorical data　4.6   Frequency data　4,7   'Survival' data　4.8   Final remarks　Appendix 4.1  Analysis with GenStat　Appendix 4.2  Analysis with S-Plus5　Normal data from designs with three or more treatments　5.1   Why do we have designs with three or more treatments?　5.2   Sequences for trials with three or more treatments　5.3   Analyses ignoring the effect of period　5.4   Allowing for period effects　5.5   Other miscellaneous issues　5.6   Recommendations　Appendix 5.1  Analysis with GenStat　Appendix 5.2  Analysis with S-Plus6  Other outcomes from designs with three or more treatments　6.1   Introduction　6.2   Analyses which take no account of period effects　6.3   Non-parametric analyses adjusting for period effects　6,4   Hodges-Lehmann type estimators　6.5   A stratified period adjusted sign test　6.6   Binary data　6.7   Other analyses　Appendix 6.1  Analysis with GenStat　Appendix 6.2  Analysis with S-Plus7  Some special designs8  Graphical and tabular presentation of cross-over trials9  Various design issues10  Mathematical approaches to carry-overReferencesAuthor indexSubject index

作者简介

Cross--over trials are an important class of design used in the pharmaceutical industry and medical research, and their use continues to grow. Cross--over Trials in Clinical Research, Second Edition has been fully updated to include the latest methodology used in the design and analysis of cross--over trials. It includes more background material, greater coverage of important statistical techniques, including Bayesian methods, and discussion of analysis using a number of statistical software packages. Comprehensive coverage of the design and analysis of cross--over trials. Each technique is carefully explained and the mathematics is kept to a minimum. Features many real and original examples, taken from the author's vast experience. Includes discussion of analysis using SAS, S--Plus and, GenStat, StatXact and Excel. Written in a style suitable for statisticians and physicians alike. Computer programs to accompany the examples in the book can be downloaded from the Web Primarily aimed at statisticians and researchers working in the pharmaceutical industry, the book will also appeal to physicians involved in clinical research and students of medical statistics.

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