9780470022740

Quantitative Methods for Health Research : A Practical Interactive Guide to Epidemiology and Statistics

by ; ;
  • ISBN13:

    9780470022740

  • ISBN10:

    0470022744

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2008-08-25
  • Publisher: Wiley-Interscience

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Supplemental Materials

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Summary

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.

Table of Contents

Preface
Acknowledgements
Philosophy of science and introduction to epidemiology
Introduction and learning objectives
Approaches to scientific research
Formulating a research question
Rates: incidence and prevalence
Concepts of prevention
Answers to self-assessment exercises
Routine data sources and descriptive epidemiology
Introduction and learning objectives
Routine collection of health information
Descriptive epidemiology
Information on the environment
Displaying, describing and presenting data
Summary of routinely available data
Descriptive epidemiology in action
Overview of epidemiological study designs
Answers to self-assessment exercises
Standardisation
Introduction and learning objectives
Health inequalities in Merseyside
Indirect standardisation: calculation of the standardised mortality ratio (SMR)
Direct standardisation
Standardisation for factors other than age
Answers to self-assessment exercises
Surveys
Introduction and learning objectives
Purpose and context
Sampling methods
The sampling frame
Sampling error, confidence intervals and sample size
Response
Measurement
Data types and presentation
Answers to self-assessment exercises
Cohort studies
Introduction and learning objectives
Why do a cohort study?
Obtaining the sample
Measurement
Follow-up
Basic presentation and analysis of results
How large should a cohort study be?
Confounding
Simple linear regression
Introduction to multiple linear regression
Answers to self-assessment exercises
Case-control studies
Introduction and learning objectives
Why do a case-control study?
Key elements of study design
Basic unmatched and matched analysis
Sample size for a case-control study
Confounding and logistic regression
Answers to self-assessment exercises
Intervention studies
Introduction and learning objectives
Why do an intervention study?
Key elements of intervention study design
The analysis of intervention studies
Testing more complex interventions
How big should the trial be?
Further aspects of intervention study design and analysis
Answers to self-assessment exercises
Life tables, survival analysis and Cox regression
Introduction and learning objectives
Survival analysis
Cox regression
Current life tables
Answers to self-assessment exercises
Systematic reviews and meta analysis
Introduction and learning objectives
The why and how of systematic reviews
The methodology of meta-analysis
Systematic reviews and meta-analyses of observational studies
The Cochrane Collaboration
Answers to self-assessment exercises
Prevention strategies and evaluation of screening
Introduction and learning objectives
Concepts of risk
Strategies of prevention
Evaluation of screening programmes
Cohort and period effects
Answers to self-assessment exercises
Probability distributions, hypothesis testing and Bayesian methods
Introduction and learning objectives
Probability distributions
Data that do not 'fit' a probability distri
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