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Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics [Mīkstie vāki]

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(University of Liverpool, UK), (University Of Liverpool), (University Of Liverpool)
  • Formāts: Paperback / softback, 554 pages, height x width x depth: 247x189x30 mm, weight: 1021 g
  • Izdošanas datums: 27-Jun-2008
  • Izdevniecība: Wiley-Interscience
  • ISBN-10: 0470022752
  • ISBN-13: 9780470022757
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Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and StatisticsPalielināt
  • Formāts: Paperback / softback, 554 pages, height x width x depth: 247x189x30 mm, weight: 1021 g
  • Izdošanas datums: 27-Jun-2008
  • Izdevniecība: Wiley-Interscience
  • ISBN-10: 0470022752
  • ISBN-13: 9780470022757
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780470022757.html
Keywords:
Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community.

Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts.

The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so.

The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.

Preface ix
Philosophy of science and introduction to epidemiology
1(28)
Introduction and learning objectives
1(1)
Approaches to scientific research
2(7)
Formulating a research question
9(3)
Rates: incidence and prevalence
12(6)
Concepts of prevention
18(3)
Answers to self-assessment exercises
21(8)
Routine data sources and descriptive epidemiology
29(82)
Introduction and learning objectives
29(1)
Routine collection of health information
30(8)
Descriptive epidemiology
38(8)
Information on the environment
46(2)
Displaying, describing and presenting data
48(30)
Summary of routinely available data
78(9)
Descriptive epidemiology in action
87(4)
Overview of epidemiological study designs
91(3)
Answers to self-assessment exercises
94(17)
Standardisation
111(18)
Introduction and learning objectives
111(1)
Health inequalities in Merseyside
111(3)
Indirect standardisation: calculation of the standardised mortality ratio (SMR)
114(5)
Direct standardisation
119(4)
Standardisation for factors other than age
123(1)
Answers to self-assessment exercises
124(5)
Surveys
129(64)
Introduction and learning objectives
129(1)
Purpose and context
130(3)
Sampling methods
133(10)
The sampling frame
143(2)
Sampling error, confidence intervals and sample size
145(15)
Response
160(4)
Measurement
164(15)
Data types and presentation
179(5)
Answers to self-assessment exercises
184(9)
Cohort studies
193(64)
Introduction and learning objectives
193(1)
Why do a cohort study?
194(2)
Obtaining the sample
196(3)
Measurement
199(3)
Follow-up
202(3)
Basic presentation and analysis of results
205(18)
How large should a cohort study be?
223(3)
Confounding
226(6)
Simple linear regression
232(11)
Introduction to multiple linear regression
243(6)
Answers to self-assessment exercises
249(8)
Case-control studies
257(50)
Introduction and learning objectives
257(2)
Why do a case-control study?
259(6)
Key elements of study design
265(8)
Basic unmatched and matched analysis
273(8)
Sample size for a case-control study
281(3)
Confounding and logistic regression
284(14)
Answers to self-assessment exercises
298(9)
Intervention studies
307(56)
Introduction and learning objectives
307(2)
Why do an intervention study?
309(3)
Key elements of intervention study design
312(6)
The analysis of intervention studies
318(9)
Testing more complex interventions
327(4)
How big should the trial be?
331(4)
Further aspects of intervention study design and analysis
335(16)
Answers to self-assessment exercises
351(12)
Life tables, survival analysis and Cox regression
363(30)
Introduction and learning objectives
363(1)
Survival analysis
364(15)
Cox regression
379(6)
Current life tables
385(4)
Answers to self-assessment exercises
389(4)
Systematic reviews and meta-analysis
393(40)
Introduction and learning objectives
393(2)
The why and how of systematic reviews
395(14)
The methodology of meta-analysis
409(13)
Systematic reviews and meta-analyses of observational studies
422(4)
The Cochrane Collaboration
426(3)
Answers to self-assessment exercises
429(4)
Prevention strategies and evaluation of screening
433(38)
Introduction and learning objectives
433(1)
Concepts of risk
434(4)
Strategies of prevention
438(8)
Evaluation of screening programmes
446(11)
Cohort and period effects
457(7)
Answers to self-assessment exercises
464(7)
Probability distributions, hypothesis testing and Bayesian methods
471(56)
Introduction and learning objectives
471(2)
Probability distributions
473(9)
Data that do not `fit' a probability distribution
482(6)
Hypothesis testing
488(27)
Choosing an appropriate hypothesis test
515(4)
Bayesian methods
519(4)
Answers to self-assessment exercises
523(4)
References 527(2)
Index 529
Nigel Bruce, PhD is Emeritus Professor of Public Health at the Department of Public Health and Policy, University of Liverpool, UK.

Daniel Pope, PhD is Senior Lecturer in Epidemiology and Public Health at the Department of Public Health and Policy, University of Liverpool, UK.

Debbi Stanistreet, PhD is Senior Lecturer and Faculty Director of Widening Participation at the Department of Public Health and Policy, University of Liverpool, UK.