Design and analysis of quality of life studies in clinical trials
著者
書誌事項
Design and analysis of quality of life studies in clinical trials
（Interdisciplinary statistics）
Chapman & Hall/CRC, c2010
2nd ed
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Design Principles and Analysis Techniques for HRQoL Clinical Trials
SAS, R, and SPSS examples realistically show how to implement methods
Focusing on longitudinal studies, Design and Analysis of Quality of Life Studies in Clinical Trials, Second Edition addresses design and analysis aspects in enough detail so that readers can apply statistical methods, such as mixed effect models, to their own studies. The author illustrates the implementation of the methods using the statistical software packages SAS, SPSS, and R.
New to the Second Edition
Data sets available for download online, allowing readers to replicate the analyses presented in the text
New chapter on testing models that involve moderation and mediation
Revised discussions of multiple comparisons procedures that focus on the integration of health-related quality of life (HRQoL) outcomes with other study outcomes using gatekeeper strategies
Recent methodological developments for the analysis of trials with missing data
New chapter on quality adjusted life-years (QALYs) and QTWiST specific to clinical trials
Additional examples of the implementation of basic models and other selected applications in R and SPSS
This edition continues to provide practical information for researchers directly involved in the design and analysis of HRQoL studies as well as for those who evaluate the design and interpret the results of HRQoL research. By following the examples in the book, readers will be able to apply the steps to their own trials.
目次
Introduction and Examples. Study Design and Protocol Development. Models for Longitudinal Studies I. Models for Longitudinal Studies II. Moderation and Mediation. Characterization of Missing Data. Analysis of Studies with Missing Data. Simple Imputation. Multiple Imputation. Pattern Mixture and Other Mixture Models. Random Effects Dependent Dropout. Selection Models. Multiple Endpoints. Composite Endpoints and Summary Measures. Quality Adjusted Life-Years (QALYs) and Q-TWiST. Analysis Plans and Reporting Results. Appendices. References.
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