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

by Bruce, Nigel; Pope, Daniel; Stanistreet, Debbi

• ISBN13: 9780470022757
• ISBN10: 0470022752
• Edition: 1st
• Format: Paperback
• Copyright: 2008-08-18
• Publisher: Wiley-Interscience

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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