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An essential, up-to-date guide to the design of studies andselection of the correct QoL instruments for observational studiesand clinical trials. Quality of Life (QoL) outcomes or Person/Patient ReportedOutcome Measures (PROMs) are now frequently being used inrandomised controlled trials (RCTs) and observational studies. Thisbook provides a practical guide to the design, analysis andinterpretation of studies that use such outcomes. QoL outcomes tend to generate data with discrete, bounded andskewed distributions. Many investigators are concerned about theappropriateness of using standard…mehr

Produktbeschreibung
An essential, up-to-date guide to the design of studies andselection of the correct QoL instruments for observational studiesand clinical trials. Quality of Life (QoL) outcomes or Person/Patient ReportedOutcome Measures (PROMs) are now frequently being used inrandomised controlled trials (RCTs) and observational studies. Thisbook provides a practical guide to the design, analysis andinterpretation of studies that use such outcomes. QoL outcomes tend to generate data with discrete, bounded andskewed distributions. Many investigators are concerned about theappropriateness of using standard statistical methods to analyseQoL data and want guidance on what methods to use. QoL outcomes arefrequently used in cross-sectional surveys and non-randomisedhealth-care evaluations. * Provides a user-friendly guide to the design and analysis ofclinical trials and observational studies in relation to QoLoutcomes. * Discusses the problems caused by QoL outcomes and presentsintervention options to help tackle them. * Guides the reader step-by-step through the selection ofappropriate QoLs. * Features exercises and solutions and a supporting websiteproviding downloadable data files. Illustrated throughout with examples and case studies drawn fromthe author's experience, this book offers statisticians andclinicians guidance on choosing between the numerous available QoLinstruments.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

  • Produktdetails
  • Verlag: John Wiley & Sons
  • Seitenzahl: 380
  • Erscheinungstermin: 26. August 2009
  • Englisch
  • ISBN-13: 9780470871911
  • Artikelnr.: 37299787
Autorenporträt
Stephen J. Walters - School of Health and Related Research, University of Sheffield. Dr Walters has had experience both in research and teaching, and is currently the Senior Lecturer in Medical Statistics at Sheffield University. He has conducted numerous grant-funded research projects, and has nearly 150 publications to his name. These include 85 articles in a range of refereed journals, 2 co-authored books, and contributed chapters in three other books.
Inhaltsangabe
Preface. 1 Introduction. Summary. 1.1 What is quality of life? 1.2 Terminology. 1.3 History. 1.4 Types of quality of life measures. 1.5 Why measure quality of life? 1.6 Further reading. 2 Measuring quality of life. Summary. 2.1 Introduction. 2.2 Principles of measurement scales. 2.3 Indicator and causal variables. 2.4 The traditional psychometric model. 2.5 Item response theory. 2.6 Clinimetricscal. 2.7 Measuring quality of life: indicator or causal items. 2.8 Developing and testing questionnaires. 2.9 Further reading. 3 Choosing a quality of life measure for your study. Summary. 3.1 Introduction. 3.2 How to choose between instruments. 3.3 Appropriateness. 3.4 Acceptability. 3.5 Feasibility. 3.6 Validity. 3.7 Reliability. 3.8 Responsiveness. 3.9 Precision. 3.10 Interpretability. 3.11 Finding quality of life instruments. 4 Design and sample size issues: How many subjects do I need for my study? Summary. 4.1 Introduction. 4.2 Significance tests, P
values and power. 4.3 Sample sizes for comparison of two independent groups. 4.4 Choice of sample size method with quality of life outcomes. 4.5 Paired data. 4.6 Equivalence/non
inferiority studies. 4.7 Unknown standard deviation and effect size. 4.8 Cluster randomized controlled trials. 4.9 Non
response. 4.10 Unequal groups. 4.11 Multiple outcomes/endpoints. 4.12 Three or more groups. 4.13 What if we are doing a survey, not a clinical trial?. 4.14 Sample sizes for reliability and method comparison studies. 4.15 Post
hoc sample size calculations. 4.16 Conclusion: Usefulness of sample size calculations. 4.17 Further reading. 5 Reliability and method comparison studies for quality of life measurements. Summary. 5.1 Introduction. 5.2 Intra
class correlation coefficient. 5.3 Agreement between individual items on a quality of life questionnaire. 5.4 Internal consistency and Cronbach's alpha. 5.5 Graphical methods for assessing reliability or agreement between two quality of life measures or assessments. 5.6 Further reading. 5.7 Technical details. 6 Summarizing, tabulating and graphically displaying quality of life outcomes. Summary. 6.1 Introduction. 6.2 Graphs. 6.3 Describing and summarizing quality of life data. 6.4 Presenting quality of life data and results in tables and graphs. 7 Cross
sectional analysis of quality of life outcomes. Summary. 7.1 Introduction. 7.2 Hypothesis testing (using P
values). 7.3 Estimation (using confidence intervals). 7.4 Choosing the statistical method. 7.5 Comparison of two independent groups. 7.6 Comparing more than two groups. 7.7 Two groups of paired observations. 7.8 The relationship between two continuous variables. 7.9 Correlation. 7.10 Regression. 7.11 Multiple regression. 7.12 Regression or correlation?. 7.13 Parametric versus non
parametric methods. 7.14 Technical details: Checking the assumptions for a linear regression analysis. 8 Randomized controlled trials. Summary. 8.1 Introduction. 8.2 Randomized controlled trials. 8.3 Protocols. 8.4 Pragmatic and explanatory trials. 8.5 Intention
to
treat and per
protocol analyses. 8.6 Patient flow diagram. 8.7 Comparison of entry characteristics. 8.8 Incomplete data. 8.9 Main analysis. 8.10 Interpretation of changes/differences in quality of life scores. 8.11 Superiority and equivalence trials. 8.12 Adjusting for other variables. 8.13 Three methods of analysis for pre
test/post
test control group designs. 8.14 Cross
over trials. 8.15 Factorial trials. 8.16 Cluster randomized controlled trials. 8.17 Further reading. 9 Exploring and modelling longitudinal quality of life data. Summary. 9.1 Introduction. 9.2 Summarizing, tabulating and graphically displaying repeated QoL assessments. 9.3 Time
by
time analysis. 9.4 Response feature analysis
the use of summary measures. 9.5 Modelling of longitudinal data. 9.6 Conclusions. 10 Advanced methods for analysing quality of life outcomes. Summary. 10.1 Introduction. 10.2 Bootstrap methods. 10.3 Bootstrap methods for confidence interval estimation. 10.4 Ordinal regression. 10.5 Comparing two independent groups: Ordinal quality of life measures (with less than 7 categories). 10.6 Proportional odds or cumulative logit model. 10.7 Continuation ratio model. 10.8 Stereotype logistic model. 10.9 Conclusions and further reading. 11 Economic evaluations. Summary. 11.1 Introduction. 11.2 Economic evaluations. 11.3 Utilities and QALYs. 11.4 Economic evaluations alongside a controlled trial. 11.5 Cost
effectiveness analysis. 11.6 Cost
effectiveness ratios. 11.7 Cost
utility analysis and cost
utility ratios. 11.8 Incremental cost per QALY. 11.9 The problem of negative (and positive) incremental cost
effectiveness ratios. 11.10 Cost
effectiveness acceptability curves. 11.11 Further reading. 12 Meta
analysis. Summary. 12.1 Introduction. 12.2 Planning a meta
analysis. 12.3 Statistical methods in meta
analysis. 12.4 Presentation of results. 12.5 Conclusion. 12.6 Further reading. 13 Practical issues. Summary. 13.1 Missing data. 13.2 Multiplicity, multi
dimensionality and multiple quality of life outcomes. 13.3 Guidelines for reporting quality of life studies. Solutions to exercises. Appendix A: Examples of questionnaires. Appendix B: Statistical tables. References. Index.