Using SAS, SPSS, and R, this book addresses design and analysis aspects in enough detail so that readers can apply statistical methods to their own longitudinal studies. This edition includes a new chapter on testing models that involve moderation and mediation, a new chapter on QALYs and QTWiST specific to clinical trials, and recent methodological developments for the analysis of trials with missing data. It also presents revised discussions of multiple comparisons procedures that focus on the integration of HRQoL outcomes with other study outcomes using gatekeeper strategies. Data sets,…mehr
Using SAS, SPSS, and R, this book addresses design and analysis aspects in enough detail so that readers can apply statistical methods to their own longitudinal studies. This edition includes a new chapter on testing models that involve moderation and mediation, a new chapter on QALYs and QTWiST specific to clinical trials, and recent methodological developments for the analysis of trials with missing data. It also presents revised discussions of multiple comparisons procedures that focus on the integration of HRQoL outcomes with other study outcomes using gatekeeper strategies. Data sets, examples, applications, and SAS, R, and SPSS code are available on the book's website.
Diane L. Fairclough is a professor in the Department of Biostatistics and Informatics in the Colorado School of Public Health and director of the Biostatistics Core of the Colorado Health Outcomes Program at the University of Colorado in Denver. She is also President of the International Society for Quality of Life Research. Dr. Fairclough's prior appointments include St. Jude Children's Research Hospital, Harvard School of Public Health, and AMC Cancer Research Center.
Inhaltsangabe
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.
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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