Nigel Bruce

Quantitative Methods for Health Research

A Practical Interactive Guide to Epidemiology and Statistics

• Gebundenes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 560
• Erscheinungstermin: 1. Mai 2008
• Englisch
• Abmessung: 246mm x 189mm x 30mm
• Gewicht: 1202g
• ISBN-13: 9780470022740
• ISBN-10: 0470022744
• Artikelnr.: 20870389

Autorenporträt

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.

Inhaltsangabe

Preface. Acknowledgements. 1. Philosophy of science and introduction to
epidemiology. Introduction and learning objectives. 1.1 Approaches to
scientific research. 1.2 Formulating a research question. 1.3 Rates:
incidence and prevalence. 1.4 Concepts of prevention. 1.5 Answers to
self-assessment exercises. 2. Routine data sources and descriptive
epidemiology. Introduction and learning objectives. 2.1 Routine collection
of health information. 2.2 Descriptive epidemiology. 2.3 Information on the
environment. 2.4 Displaying, describing and presenting data. 2.5 Summary of
routinely available data. 2.6 Descriptive epidemiology in action. 2.7
Overview of epidemiological study designs. 2.8 Answers to self-assessment
exercises. 3. Standardisation. Introduction and learning objectives. 3.1
Health inequalities in Merseyside. 3.2 Indirect standardisation:
calculation of the standardised mortality ratio (SMR). 3.3 Direct
standardisation. 3.4 Standardisation for factors other than age. 3.5
Answers to self-assessment exercises. 4. Surveys. Introduction and learning
objectives. 4.1 Purpose and context. 4.2 Sampling methods. 4.3 The sampling
frame. 4.4 Sampling error, confidence intervals and sample size . 4.5
Response. 4.6 Measurement. 4.7 Data types and presentation. 4.8 Answers to
self-assessment exercises. 5. Cohort studies. Introduction and learning
objectives. 5.1 Why do a cohort study?. 5.2 Obtaining the sample. 5.3
Measurement. 5.4 Follow-up. 5.5 Basic presentation and analysis of results.
5.6 How large should a cohort study be?. 5.7 Confounding. 5.8 Simple linear
regression. 5.9 Introduction to multiple linear regression. 5.10 Answers to
self-assessment exercises. 6. Case-control studies. Introduction and
learning objectives. 6.1 Why do a case-control study?. 6.2 Key elements of
study design. 6.3 Basic unmatched and matched analysis. 6.4 Sample size for
a case-control study. 6.5 Confounding and logistic regression. 6.6 Answers
to self-assessment exercises. 7. Intervention studies. Introduction and
learning objectives. 7.1 Why do an intervention study?. 7.2 Key elements of
intervention study design. 7.3 The analysis of intervention studies. 7.4
Testing more complex interventions. 7.5 How big should the trial be?. 7.6
Further aspects of intervention study design and analysis. 7.7 Answers to
self-assessment exercises. 8. Life tables, survival analysis and Cox
regression. Introduction and learning objectives. 8.1 Survival analysis.
8.2 Cox regression. 8.3 Current life tables. 8.4 Answers to self-assessment
exercises. 9. Systematic reviews and meta analysis. Introduction and
learning objectives. 9.1 The why and how of systematic reviews. 9.2 The
methodology of meta-analysis. 9.3 Systematic reviews and meta-analyses of
observational studies. 9.4 The Cochrane Collaboration. 9.5 Answers to
self-assessment exercises. 10. Prevention strategies and evaluation of
screening . Introduction and learning objectives. 10.1 Concepts of risk.
10.2 Strategies of prevention. 10.3 Evaluation of screening programmes.
10.4 Cohort and period effects. 10.5 Answers to self-assessment exercises.
11. Probability distributions, hypothesis testing and Bayesian methods.
Introduction and learning objectives. 11.1 Probability distributions. 11.2
Data that do not 'fit' a probability distribution. 11.3 Hypothesis testing.
11.4 Choosing an appropriate hypothesis test. 11.5 Bayesian methods. 11.6
Answers to self-assessment exercises. Bibliography. Index.