Buch, Englisch, 392 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 798 g
Reihe: Statistics in Practice
Buch, Englisch, 392 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 798 g
Reihe: Statistics in Practice
ISBN: 978-0-470-66636-4
Verlag: Wiley
Understanding Biostatistics looks at the fundamentals of biostatistics, using elementary statistics to explore the nature of statistical tests.
This book is intended to complement first-year statistics and biostatistics textbooks. The main focus here is on ideas, rather than on methodological details. Basic concepts are illustrated with representations from history, followed by technical discussions on what different statistical methods really mean. Graphics are used extensively throughout the book in order to introduce mathematical formulae in an accessible way.
Key features:
- Discusses confidence intervals and p-values in terms of confidence functions.
- Explains basic statistical methodology represented in terms of graphics rather than mathematical formulae, whilst highlighting the mathematical basis of biostatistics.
- Looks at problems of estimating parameters in statistical models and looks at the similarities between different models.
- Provides an extensive discussion on the position of statistics within the medical scientific process.
- Discusses distribution functions, including the Guassian distribution and its importance in biostatistics.
This book will be useful for biostatisticians with little mathematical background as well as those who want to understand the connections in biostatistics and mathematical issues.
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
Weitere Infos & Material
Preface ix
1 Statistics and medical science 1
1.1 Introduction 1
1.2 On the nature of science 3
1.3 How the scientific method uses statistics 5
1.4 Finding an outcome variable to assess your hypothesis 7
1.5 How we draw medical conclusions from statistical results 8
1.6 A few words about probabilities 13
1.7 The need for honesty: the multiplicity issue 16
1.8 Prespecification and p-value history 19
1.9 Adaptive designs: controlling the risks in an experiment 21
1.10 The elusive concept of probability 23
1.11 Comments and further reading 26
References 27
2 Observational studies and the need for clinical trials 29
2.1 Introduction 29
2.2 Investigations of medical interventions and risk factors 29
2.3 Observational studies and confounders 33
2.4 The experimental study 39
2.5 Population risks and individual risks 42
2.6 Confounders, Simpson’s paradox and stratification 44
2.7 On incidence and prevalence in epidemiology 51
2.8 Comments and further reading 53
References 54
3 Study design and the bias issue 57
3.1 Introduction 57
3.2 What bias is all about 58
3.3 The need for a representative sample: on selection bias 58
3.4 Group comparability and randomization 61
3.5 Information bias in a cohort study 65
3.6 The study, or placebo, effect 68
3.7 The curse of missing values 70
3.8 Approaches to data analysis: avoiding self-inflicted bias 75
3.9 On meta-analysis and publication bias 79
3.10 Comments and further reading 81
References 82
4 The anatomy of a statistical test 85
4.1 Introduction 85
4.2 Statistical tests, medical diagnosis and Roman law 85
4.3 The risks with medical diagnosis 87
4.3.1 Medical diagnosis based on a single test 87
4.3.2 Bayes’ theorem and the use and misuse of screening tests 89
