Basic Biostatistics for Geneticists and Epidemiologists - Elston, Robert C

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Auteur(s) : Elston, Robert C - Johnson, William

Editeur : John Wiley & Sons

Langue : Anglais

Parution : 01/12/2008

Format : Moyen, de 350g à 1kg

Nombre de pages : 384.0

ISBN : 0470024909

Résumé :

Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful Essentials of Biostatistics has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures.

This Book:

• Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares.
• Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research.
• Is illustrated throughout with simple examples to clarify the statistical methodology.
• Explains Bayes' theorem pictorially.
• Features exercises, with answers to alternate questions, enabling use as a course text.

Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.

...

Biographie:

Robert C. Elston Department of Epidemiology and Biostatistics, Case Western Reserve University, USA.

William D. Johnson Pennington Biomedical Research Center, Louisiana State University, USA.

...

Sommaire:

Preface ix

1 Introduction: The Role and Relevance of Statistics, Genetics and Epidemiology In Medicine 3

Why Biostatistics? 3

What Exactly is (Are) Statistics? 5

Reasons for Understanding Statistics 6

What Exactly is Genetics? 8

What Exactly is Epidemiology? 10

How Can a Statistician Help Geneticists and Epidemiologists? 11

Disease Prevention versus Disease Therapy 12

A Few Examples: Genetics, Epidemiology and Statistical Inference 12

Summary 14

References 15

2 Populations, Samples, and Study Design 19

The Study of Cause and Effect 19

Populations, Target Populations and Study Units 21

Probability Samples and Randomization 23

Observational Studies 25

Family Studies 27

Experimental Studies 28

Quasi-Experimental Studies 36

Summary 37

Further Reading 38

Problems 38

3 Descriptive Statistics 45

Why Do We Need Descriptive Statistics? 45

Scales of Measurement 46

Tables 47

Graphs 49

Proportions and Rates 55

Relative Measures of Disease Frequency 58

Sensitivity, Specificity and Predictive Values 61

Measures of Central Tendency 62

Measures of Spread or Variability 64

Measures of Shape 67

Summary 68

Further Reading 70

Problems 70

4 The Laws of Probability 79

Definition of Probability 79

The Probability of Either of Two Events: A or B 82

The Joint Probability of Two Events: A and B 83

Examples of Independence, Nonindependence and Genetic Counseling 86

Bayes' Theorem 89

Likelihood Ratio 97

Summary 98

Further Reading 99

Problems 99

5 Random Variables and Distributions 107

Variability and Random Variables 107

Binomial Distribution 109

A Note about Symbols 112

Poisson Distribution 113

Uniform Distribution 114

Normal Distribution 116

Cumulative Distribution Functions 119

The Standard Normal (Gaussian) Distribution 120

Summary 122

Further Reading 123

Problems 123

6 Estimates and Confidence Limits 131

Estimates and Estimators 131

Notation for Population Parameters, Sample Estimates, and Sample Estimators 133

Properties of Estimators 134

Maximum Likelihood 135

Estimating Intervals 137

Distribution of the Sample Mean 138

Confidence Limits 140

Summary 146

Problems 148

7 Significance Tests and Tests of Hypotheses 155

Principle of Significance Testing 155

Principle of Hypothesis Testing 156

Testing a Population Mean 157

One-Sided versus Two-Sided Tests 160

Testing a Proportion 161

Testing the Equality of Two Variances 165

Testing the Equality of Two Means 167

Testing the Equality of Two Medians 169

Validity and Power 172

Summary 176

Further Reading 178

Problems 178

8 Likelihood Ratios, Bayesian Methods and Multiple Hypotheses 187

Likelihood Ratios 187

Bayesian Methods 190

Bayes' Factors 192

Bayesian Estimates and Credible Intervals 194

The Multiple Testing Problem 195

Summary 198

Problems 199

9 The Many Uses of Chi-Square 203

The Chi-Square Distribution 203

Goodness-of-Fit Tests 206

Contingency Tables 209

Inference About the Variance 219

Combining p-Values 220

Likelihood Ratio Tests 221

Summary 223

Further Reading 225

Problems 225

10 Correlation and Regression 233