Atnaujinkite slapukų nuostatas

El. knyga: Quality of Life Outcomes in Clinical Trials and Health-Care Evaluation: A Practical Guide to Analysis and Interpretation

5.00/5 (2 ratings by Goodreads)
(University of Sheffield)
  • Formatas: PDF+DRM
  • Serija: Statistics in Practice
  • Išleidimo metai: 10-Sep-2009
  • Leidėjas: John Wiley & Sons Inc
  • Kalba: eng
  • ISBN-13: 9780470871911
Kitos knygos pagal šią temą:
Quality of Life Outcomes in Clinical Trials and Health-Care Evaluation: A Practical Guide to Analysis and InterpretationDidesnis paveikslėlis
  • Formatas: PDF+DRM
  • Serija: Statistics in Practice
  • Išleidimo metai: 10-Sep-2009
  • Leidėjas: John Wiley & Sons Inc
  • Kalba: eng
  • ISBN-13: 9780470871911
Kitos knygos pagal šią temą:

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

Walters (health and related research, U. of Sheffield, England) explains how to design, analyze, and interpret randomized controlled trials that use quality-of-life outcomes or person/patient reported outcome measures. Because researchers are increasingly using off-the-shelf quality-of-life instruments, he provides practical advice on choosing between the many that are now available. He addressed readers in either professional or academic settings who are going to collect and analyze their own data, and are familiar with basic statistical concepts such as hypothesis testing, confidence intervals, simple statistical tests, and simple linear regression. Among his topics are design and sample size issues, the cross-sectional analysis of quality-of-life outcomes, exploring and modelling longitudinal data, economic evaluations, and meta-analysis. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)

An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials.

Quality of Life (QoL) outcomes or Person/Patient Reported Outcome Measures (PROMs) are now frequently being used in randomised controlled trials (RCTs) and observational studies. This book provides a practical guide to the design, analysis and interpretation of studies that use such outcomes.

QoL outcomes tend to generate data with discrete, bounded and skewed distributions. Many investigators are concerned about the appropriateness of using standard statistical methods to analyse QoL data and want guidance on what methods to use. QoL outcomes are frequently used in cross-sectional surveys and non-randomised health-care evaluations.

  • Provides a user-friendly guide to the design and analysis of clinical trials and observational studies in relation to QoL outcomes.
  • Discusses the problems caused by QoL outcomes and presents intervention options to help tackle them.
  • Guides the reader step-by-step through the selection of appropriate QoLs.
  • Features exercises and solutions and a supporting website (www.wiley.com/go/walters) providing downloadable data files.

Illustrated throughout with examples and case studies drawn from the author’s experience, this book offers statisticians and clinicians guidance on choosing between the numerous available QoL instruments.

Recenzijos

"The book covers a wide range of issues and techniques. ... Subjects are exposed clearly, with the obvious aim of being accessible to clinicians unfamiliar with mathematical formalism, and the methods are nicely illustrated with QoL data examples." (Journal of Biopharmaceutical Statistics, April 2010)

Preface xi
Introduction
1(12)
Summary
1(1)
What is quality of life?
1(1)
Terminology
2(1)
History
2(2)
Types of quality of life measures
4(6)
Why measure quality of life?
10(1)
Further reading
11(2)
Measuring quality of life
13(18)
Summary
13(1)
Introduction
13(1)
Principles of measurement scales
13(2)
Scales and items
13(1)
Constructs and latent variables
14(1)
Indicator and causal variables
15(1)
Indicator variables
15(1)
Causal variables
15(1)
Why do we need to worry about the distinction between indicator and causal items?
16(1)
Single-item versus multi-item scales
16(1)
The traditional psychometric model
16(1)
Psychometrics and QoL scales
17(1)
Item response theory
17(1)
Traditional scales versus IRT
18(1)
Clinimetric scales
18(1)
Measuring quality of life: Indicator or causal items
19(1)
Developing and testing questionnaires
19(11)
Specify the research question and define the target population
19(1)
Identify concepts
20(1)
Create instrument
21(5)
Assess measurement properties
26(4)
Modify instrument
30(1)
Further reading
30(1)
Choosing a quality of life measure for your study
31(24)
Summary
31(1)
Introduction
31(1)
How to choose between instruments
31(2)
Appropriateness
33(1)
Acceptability
33(1)
Feasibility
34(1)
Validity
35(3)
Tests for criterion validity
35(1)
Tests for face and content validity
36(1)
Tests for construct validity
36(2)
Reliability
38(6)
Repeatability reliability
40(1)
Graphical methods for assessing reliability between two repeated measurements
40(2)
Internal reliability or internal consistency reliability
42(2)
Responsiveness
44(5)
Floor and ceiling effects
44(5)
Precision
49(2)
Interpretability
51(2)
Finding quality of life instruments
53(2)
Design and sample size issues: How many subjects do I need for my study?
55(36)
Summary
55(1)
Introduction
55(1)
Significance tests, P-values and power
56(2)
Sample sizes for comparison of two independent groups
58(11)
Normally distributed continuous data - comparing two means
58(3)
Transformations
61(1)
Comparing two groups with continuous data using non-parametric methods
61(2)
Dichotomous categorical data - comparing two proportions
63(3)
Ordered categorical (ordinal) data
66(3)
Choice of sample size method with quality of life outcomes
69(1)
Paired data
70(3)
Paired continuous data - comparison of means
70(2)
Paired binary data - comparison of proportions
72(1)
Equivalence/non-inferiority studies
73(2)
Continuous data - comparing the equivalence of two means
74(1)
Binary data - comparing the equivalence of two proportions
75(1)
Unknown standard deviation and effect size
75(1)
Tips on obtaining the standard deviation
76(1)
Cluster randomized controlled trials
76(1)
Non-response
77(1)
Unequal groups
77(2)
Multiple outcomes/endpoints
79(1)
Three or more groups
80(1)
What if we are doing a survey, not a clinical trial?
80(5)
Sample sizes for surveys
80(1)
Confidence intervals for estimating the mean QoL of a population
81(1)
Confidence intervals for a proportion
82(3)
Sample sizes for reliability and method comparison studies
85(1)
Post-hoc sample size calculations
86(1)
Conclusion: Usefulness of sample size calculations
86(1)
Further reading
86(5)
Reliability and method comparison studies for quality of life measurements
91(18)
Summary
91(1)
Introduction
91(1)
Intra-class correlation coefficient
92(3)
Inappropriate method
94(1)
Agreement between individual items on a quality of life questionnaire
95(3)
Binary data: Proportion of agreement
95(1)
Binary data: Kappa
95(1)
Ordered categorical data: Weighted kappa
96(2)
Internal consistency and Cronbach's alpha
98(1)
Graphical methods for assessing reliability or agreement between two quality of life measures or assessments
99(3)
Further reading
102(1)
Technical details
102(7)
Calculation of ICC
102(1)
Calculation of kappa
103(1)
Calculation of weighted kappa
104(1)
Calculation of Cronbach's alpha
104(5)
Summarizing, tabulating and graphically displaying quality of life outcomes
109(24)
Summary
109(1)
Introduction
109(1)
Graphs
110(6)
Dot plots
112(1)
Histograms
112(2)
Box-and-whisker plot
114(2)
Scatter plots
116(1)
Describing and summarizing quality of life data
116(6)
Measures of location
117(2)
Measures of spread
119(3)
Presenting quality of life data and results in tables and graphs
122(11)
Tables for summarizing QoL outcomes
122(2)
Tables for multiple outcome measures
124(2)
Tables and graphs for comparing two groups
126(3)
Profile graphs
129(4)
Cross-sectional analysis of quality of life outcomes
133(48)
Summary
133(1)
Introduction
133(1)
Hypothesis testing (using P-values)
134(3)
Estimation (using confidence intervals)
137(1)
Choosing the statistical method
138(1)
Comparison of two independent groups
138(8)
Independent samples t-test for continuous outcome data
140(4)
Mann-Whitney U-test
144(2)
Comparing more than two groups
146(4)
One-way analysis of variance
147(3)
The Kruskal-Wallis test
150(1)
Two groups of paired observations
150(7)
Paired t-test
153(4)
Wilcoxon test
157(1)
The relationship between two continuous variables
157(3)
Correlation
160(5)
Regression
165(3)
Multiple regression
168(3)
Regression or correlation?
171(1)
Parametric versus non-parametric methods
171(2)
Technical details: Checking the assumptions for a linear regression analysis
173(8)
Randomized controlled trials
181(36)
Summary
181(1)
Introduction
181(1)
Randomized controlled trials
182(1)
Protocols
182(1)
Pragmatic and explanatory trials
182(1)
Intention-to-treat and per-protocol analyses
183(3)
Patient flow diagram
186(1)
Comparison of entry characteristics
186(3)
Incomplete data
189(2)
Main analysis
191(5)
Interpretation of changes/differences in quality of life scores
196(1)
Superiority and equivalence trials
197(2)
Adjusting for other variables
199(3)
Three methods of analysis for pre-test/post-test control group designs
202(1)
Cross-over trials
203(3)
Factorial trials
206(3)
Cluster randomized controlled trials
209(1)
Further reading
210(7)
Exploring and modelling longitudinal quality of life data
217(32)
Summary
217(1)
Introduction
217(1)
Summarizing, tabulating and graphically displaying repeated QoL assessments
218(4)
Time-by-time analysis
222(1)
Response feature analysis - the use of summary measures
223(6)
Area under the curve
223(4)
Acupuncture study - analysis of covariance
227(2)
Modelling of longitudinal data
229(14)
Autocorrelation
231(1)
Repeated measures analysis of variance
232(1)
Marginal general linear models - generalized estimating equations
232(5)
Random effects models
237(2)
Random effects versus marginal modelling
239(2)
Use of marginal and random effects models to analyse data from a cluster RCT
241(2)
Conclusions
243(6)
Advanced methods for analysing quality of life outcomes
249(16)
Summary
249(1)
Introduction
249(2)
Bootstrap methods
251(1)
Bootstrap methods for confidence interval estimation
251(4)
Ordinal regression
255(2)
Comparing two independent groups: Ordinal quality of life measures (with less than 7 categories)
257(1)
Proportional odds or cumulative logit model
258(1)
Continuation ratio model
259(1)
Stereotype logistic model
260(4)
Conclusions and further reading
264(1)
Economic evaluations
265(12)
Summary
265(1)
Introduction
265(1)
Economic evaluations
266(1)
Utilities and QALYs
266(1)
Economic evaluations alongside a controlled trial
267(1)
Cost-effectiveness analysis
267(1)
Cost-effectiveness ratios
268(1)
Cost-utility analysis and cost-utility ratios
269(1)
Incremental cost per QALY
270(2)
The problem of negative (and positive) incremental cost-effectiveness ratios
272(1)
Cost-effectiveness acceptability curves
273(2)
Further reading
275(2)
Meta-analysis
277(20)
Summary
277(1)
Introduction
277(1)
Planning a meta-analysis
278(4)
Is a meta-analysis appropriate?
279(1)
Combining the results of different studies
279(1)
Choosing the appropriate statistical method
280(2)
Statistical methods in meta-analysis
282(11)
The choice of effect measure: What outcome measures am I combining?
282(1)
Model choice: fixed or random?
283(2)
Homogeneity
285(1)
Fixed effects model
285(2)
Forest plots
287(2)
Random effects
289(1)
Funnel plots
289(4)
Presentation of results
293(1)
Conclusion
294(1)
Further reading
295(2)
Practical issues
297(22)
Summary
297(1)
Missing data
297(13)
Why do missing data matter?
297(1)
Methods for missing items within a form
298(2)
Methods for missing forms
300(8)
The regulator's view on statistical considerations for patient-level missing data
308(1)
Conclusions and further reading on missing QoL data
309(1)
Multiplicity, multi-dimensionality and multiple quality of life outcomes
310(4)
Which multiple comparison procedure to use?
312(2)
Guidelines for reporting quality of life studies
314(5)
Solutions to exercises 319(16)
Appendix A: Examples of questionnaires 335(10)
Appendix B: Statistical tables 345(6)
References 351(10)
Index 361
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.
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
Pastovi nuoroda: https://www.kriso.lt/db/97804708719112e.html
Raktažodžiai: