The Assessment, Analysis and Interpretation of Patient-reported Outcomes
Slutsåld
"The updates in this edition retain the high standards set forth in the original book. This book is written at a level that is understandable to the relative novice in terms of QOL assessment and provides excellent examples, but also has details and formulas to satisfy methologically advanced researchers. This book is excellent reference for anyone needing a comprehensive but accessible text on QOL and PROs assessment." (Biometrics, September 2008) "This book is exceptionally well written and nicely illustrated and has an excellent style, all of which make it a pleasure to read." (Journal of the American Statistical Association, September 2008)
Peter Fayers, University of Aberdeen Medical School, UK, Norwegian University of Science and Technology (NTNU), Tronheim, Norway David Machin, Division of Clinical Trials and Epidemiological Sciences, National Cancer Center, Singapore, School of Health and Related Research, University of Sheffield, England United Kingdom Children's Cancer Study Group (UKCCSG), University of Leicester,UK
Preface to the first edition. Preface to the second edition. List of abbreviations. Part A. Introduction. 1. Introduction. 1.1 Patient-reported outcomes? 1.2 What is quality of life? 1.3 Historical development. 1.4 Why measure quality of life? 1.5 Which clinical trials should assess quality of life? 1.6 How to measure quality of life. 1.7 Instruments. 1.8 Conclusions. 2. Principles of measurement scales. 2.1 Introduction. 2.2 Scales and items. 2.3 Constructs and latent variables. 2.4 Indicator variables and causal variables. 2.5 Single global questions versus multi-item scales. 2.6 Single-item versus multi-item scales. 2.7 Psychometrics and item response theory. 2.8 Psychometric versus clinimetric scales. 2.9 Sufficient causes and necessary causes. 2.10 Discriminative, evaluative and predictive instruments. 2.11 Measuring quality of life: indicator or causal items? 2.12 Conclusions. Part B. Developing and Testing Questionnaires. 3. Developing a questionnaire. 3.1 Introduction. 3.2 General issues. 3.3 Defining the target population. 3.4 Item generation. 3.5 Qualitative methods. 3.6 Forming scales. 3.7 Multi-item scales. 3.8 Wording of questions. 3.9 Face and content validity of the proposed questionnaire. 3.10 Pre-testing the questionnaire. 3.11 Strategies for validation. 3.12 Translation. 3.13 Field testing. 3.14 Conclusions. 3.15 Further reading. 4. Scores and measurements: validity, reliability, sensitivity. 4.1 Introduction. 4.2 Content validity. 4.3 Criterion validity. 4.4 Construct validity. 4.5 Reliability. 4.6 Sensitivity and responsiveness. 4.7 Conclusions. 5. Multi-item scales. 5.1 Introduction. 5.2 Significance tests. 5.3 Correlations. 5.4 Construct validity. 5.5 Cronbach's α and internal consistency. 5.6 Implications for causal items. 5.7 Conclusions. 6. Factor analysis and structural equation modelling. 6.1 Introduction. 6.2 Correlation patterns. 6.3 Path diagrams. 6.4 Factor analysis. 6.5 Factor analysis of the HADS questionnaire. 6.6 Uses of factor analysis. 6.7 Applying factor analysis: choices and decisions. 6.8 Assumptions for factor analysis. 6.9 Factor analysis in QoL research. 6.10 Limitations of correlation-based analysis. 6.11 Causal models. 6.12 Confirmatory factor analysis and structural equation modelling. 6.13 Conclusions. 6.14 Further reading and software. 7. Item response theory and differential item functioning. 7.1 Introduction. 7.2 Item characteristic curves . 7.3 Logistic models. 7.4 Fitting item response theory models: tips. 7.5 Test design. 7.6 IRT versus traditional and Guttman scales. 7.7 Polytomous item response theory models. 7.8 Differential item functioning. 7.9 Quantifying differential item functioning. 7.10 Exploring differential item functioning: tips. 7.11 Conclusions. 7.12 Further reading and software. 8. Item banks, item listing and computer-adaptive tests. 8.1 Introduction. 8.2 Item bank. 8.3 Item calibration. 8.4 Item linking and test equating. 8.5 Test information. 8.6 Computer-adaptive testing. 8.7 Stopping rules and simulations. 8.8 Computer-adaptive testing software. 8.9 Unresolved issues. 8.10 Computer-assisted tests. 8.11 Conclusions. 8.12 Further reading. Part C. Clinical Trials. 9. Choosing and scoring questionnaires. 9.1 Introduction. 9.2 Generic versus specific. 9.3 Finding instruments. 9.4 Choice of instrument. 9.5 Adding ad-hoc items. 9.6 Scoring multi-item scales. 9.7 Conclusions. 9.8 Further reading. 10. Clinical trials. 10.1 Introduction. 10.2 Basic design issues. 10.3 Compliance. 10.4 Administering a quality-of-life assessment. 10.5 Recommendations for writing protocols. 10.6 Standard operating procedures. 10.7 Summary and checklist. 11. Sample sizes. 11.1 Introduction. 11.2 Significance tests, p-values and power. 11.3 Estimating sample size. 11.4 Comparing two groups. 11.5 Comparison with a reference population. 11.6 Equivalence studies. 11.7 Choice of sample size method. 11.8 Multiple endpoints. 11.9 Specifying the target difference. 11.10 Sample size estim