Description
Springer Statistical Methods for Quality of Life Studies Design Measurements and Analysis 1st Editon 2002 Hardbound by Mounir Mesbah, Bernard F. Cole, Mei-Ling Ting Lee
On October 16 and 17, 2000, we hosted an international workshop entitled 'Statistical Design, Measurement, and Analysis of Health Related Quality of Life.' The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters. 1: Measurement, Scale Development, and Study Design.- Regulatory Aspects of Quality of Life.- Biases in the Retrospective Calculation of Reliability and Responsiveness from Longitudinal Studies.- Application of the Multiattribute Utility Theory to the Development of a Preference based Health-Related Quality of Life Instrument.- Strategy and Methodology for Choice of Items in Psychometric Measurement: Designing a Quality of Life Instrument for Hip and Knee Osteoarthritis.- Conception, Development and Validation of Instruments for Quality of Life Assessment: An Overview.- Methodological Issues in the Analysis of Quality of Life Data in Clinical Trials: Illustrations from the National Surgical Adjuvant Breast and Bowel Project (NSABP) Breast Cancer Prevention Trial.- Disease-Specific Versus Generic Measurement of Health-Related Quality of Life in Cross-Sectional and Longitudinal Studies: an Inpatient Investigation of the SF-36 and Four Disease-Specific Instruments.- 2: Analysis and Interpretation of Multiple Endpoints.- Analyzing Longitudinal Health-Related Quality of Life Data: Missing Data and Imputation Methods.- Comparison of Treatments with Multiple Outcomes.- The Use of Soft Endpoints in Clinical Trials: The Search for Clinical Significance.- 3: Item Response Theory and Rasch Models.- Parametric and Nonparametric Item Response Theory Models in Health Related Quality of Life Measurement.- Questionnaire Reliability Under the Rasch Model.- Item Response Theory (IRT): Applications in Quality of Life Measurement, Analysis and Interpretation.- Graphical Rasch Models.- 4: Joint Analysis of Quality of Life and Survival.- Semi-Markov Models for Quality of Life Data with Censoring.- A Model Relating Quality of Life to Latent Health Status and Survival.- Applying Survival Data Methodology to Analyze Longitudinal Quality of Life Data.- Latent Class Models to Describe Changes Over Time: A Case Study.- 5: Quality-Adjusted Survival Analysis and Related Methods.- Prevalence Analysis of Recurrent and Transient Health States in Quality of Life Studies.- Measures of Quality Adjusted Life and Quality of Life Deficiency: Statistical Perspectives.- Quality-Adjusted Survival Analysis in Cancer Clinical Trials.- 6: Methods for Informatively Missing Longitudinal quality-of-llfe data.- Handling of Missing Data.- Guidelines For Administration of Self-Reported Health-Related Quality of Questionnaires: How to Minimize Avoidable Missing Data?.- Joint Analysis of Survival and Nonignorable Missing Longitudinal Quality-of-Life Data.- Multiple Imputation for Non-Random Missing Data in Longitudinal Studies of Health-Related Quality of Life.- Strategies to Fit Pattern-Mixture Models.- Analysis of Longitudinal Quality of Life Data with Informative Dropout.