Introduction to Research Methods and Data Analysis in the Health Sciences |
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| Author:
| Hagger-Johnson, Gareth |
| ISBN: | 978-0-273-76384-0 |
| Publication Date: | Jun 2014 |
| Publisher: | Routledge
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| Book Format: | Hardback |
| List Price: | AUD $84.99 |
Book Description:
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Whilst the 'health sciences' are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences - and students are expected increasingly to do both.
Introduction to Research Methods and Data Analysis in the Health...
More Description
Whilst the 'health sciences' are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences - and students are expected increasingly to do both.
Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research - critical numbers, critical appraisal of existing research, and conducting new research - this accessible textbook introduces:
- Descriptive statistics
- Measures of association for categorical and continuous outcomes
- Confounding, effect modification, mediation and causal inference
- Critical appraisal
- Searching the literature
- Randomised controlled trials
- Cohort studies
- Case-control studies
- Research ethics and data management
- Dissemination and publication
- Linear regression for continuous outcomes
- Logistic regression for categorical outcomes.
A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book's exercises and activities.
Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences.