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TitleRecent Advances in Clinical Trial Design and Analysis [electronic resource] / edited by Peter F. Thall
ImprintBoston, MA : Springer US : Imprint: Springer, 1995
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Descript X, 258 p. online resource


Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data. Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much greater support to medical researchers working in both clinical and laboratory settings. As our collective toolkit of techniques for analyzing data has grown, it has become increasingly difficult for biostatisticians to keep up with all the developments in our own field. Recent Advances in Clinical Trial Design and Analysis brings together biostatisticians doing cutting-edge research and explains some of the more recent developments in biostatistics to clinicians and scientists who work in clinical trials


1. The alpha spending function approach to interim data analyses -- 2. Issues in the design and analysis of AIDS clinical trials -- 3. Recent developments in the design of phase II clinical trials -- 4. Multivariate failure time data -- 5. Goodness-of-fit and diagnostics for proportional hazards regression models -- 6. A review of tree-based prognostic models -- 7. Decision analysis and Bayesian methods in clinical trials -- 8. A Bayesian model for evaluating specificity of treatment effects in clinical trials -- 9. The exact analysis of contingency tables in medical research -- 10. Stratified-adjusted versus unstratified assessment of sample size and power for analyses of proportions -- 11. Quality-of-life assessment in clinical trials

Medicine Cancer research Oncology Statistics Medicine & Public Health Oncology Cancer Research Statistics for Life Sciences Medicine Health Sciences


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