Statistical estimation of epidemiological risk / Kung-Jong Lui.

Format:

Book

Author/Creator:

Lui, Kung-Jong.

Series:

Statistics in practice

Language:

English

Subjects (All):

Risk Assessment--methods.

Statistics as Topic--methods.

Epidemiology--Statistical methods.

Epidemiology.

Medical Subjects:

Risk Assessment--methods.

Statistics as Topic--methods.

Physical Description:

xv, 193 pages ; 24 cm.

Place of Publication:

Chichester ; Hoboken, NJ : Wiley, [2004]

Summary:

"Statistical Estimation of Epidemiological Risk" provides coverage of the most important epidemiological indices, and includes recent developments in the field. A useful reference source for biostatisticians and epidemiologists working in disease prevention, as the chapters are self-contained and feature numerous real examples. It has been written at a level suitable for public health professionals with a limited knowledge of statistics.

Other key features include: Provides comprehensive coverage of the key epidemiological indices. Includes coverage of various sampling methods, and pointers to where each should be used. Includes up-to-date references and recent developments in the field. Features many real examples, emphasising the practical nature of the book. Each chapter is self-contained, allowing the book to be used as a useful reference source. Includes exercises, enabling use as a course text.

Contents:

1 Population Proportion or Prevalence 1

1.1 Binomial sampling 2

1.2 Cluster sampling 4

1.3 Inverse sampling 8

2 Risk Difference 15

2.1 Independent binomial sampling 16

2.2 A series of independent binomial sampling procedures 19

2.2.1 Summary interval estimators 19

2.2.2 Test for the homogeneity of risk difference 21

2.3 Independent cluster sampling 24

2.4 Paired-sample data 27

2.5 Independent negative binomial sampling (inverse sampling) 31

2.6 Independent poisson sampling 34

2.7 Stratified poisson sampling 36

3 Relative Difference 47

3.1 Independent binomial sampling 48

3.2 A series of independent binomial sampling procedures 50

3.2.1 Asymptotic interval estimators 50

3.2.2 Test for the homogeneity of relative difference 52

3.3 Independent cluster sampling 54

3.4 Paired-sample data 56

3.5 Independent inverse sampling 58

4 Relative Risk 65

4.1 Independent binomial sampling 66

4.2 A series of independent binomial sampling procedures 68

4.2.1 Asymptotic interval estimators 68

4.2.2 Test for the homogeneity of risk ratio 70

4.3 Independent cluster sampling 71

4.4 Paired-sample data 73

4.5 Independent inverse sampling 75

4.5.1 Uniformly minimum variance unbiased estimator of relative risk 75

4.5.2 Interval estimators of relative risk 77

4.6 Independent poisson sampling 78

4.7 Stratified poisson sampling 80

5 Odds Ratio 89

5.1 Independent binomial sampling 91

5.1.1 Asymptotic interval estimators 91

5.1.2 Exact confidence interval 93

5.2 A series of independent binomial sampling procedures 94

5.2.1 Asymptotic interval estimators 95

5.2.2 Exact confidence interval 97

5.2.3 Test for homogeneity of the odds ratio 98

5.3 Independent cluster sampling 99

5.4 One-to-one matched sampling 102

5.5 Logistic modeling 104

5.5.1 Estimation under multinomial or independent binomial sampling 105

5.5.2 Estimation in the case of paired-sample data 107

5.6 Independent inverse sampling 108

5.7 Negative multinomial sampling for paired-sample data 110

6 Generalized Odds Ratio 119

6.1 Independent multinomial sampling 119

6.2 Data with repeated measurements (or under cluster sampling) 122

6.3 Paired-sample data 126

6.4 Mixed negative multinomial and multinomial sampling 129

7 Attributable Risk 133

7.1 Study designs with no confounders 134

7.1.1 Cross-sectional sampling 134

7.1.2 Case

control studies 136

7.2 Study designs with confounders 138

7.2.1 Cross-sectional sampling 138

7.2.2 Case

control studies 142

7.3 Case

control studies with matched pairs 145

7.4 Multiple levels of exposure in case

control studies 148

7.5 Logistic modeling in case

control studies 151

7.5.1 Logistic model containing only the exposure variables of interest 151

7.5.2 Logistic regression model containing both exposure and confounding variables 153

7.6 Case

control studies under inverse sampling 156

8 Number Needed to Treat 167

8.1 Independent binomial sampling 168

8.2 A series of independent binomial sampling procedures 171

8.3 Independent cluster sampling 173

8.4 Paired-sample data 175

Appendix Maximum Likelihood Estimator and Large-Sample Theory 181

A.1 The maximum likelihood estimator, Wald's test, the score test, and the asymptotic likelihood ratio test 181

A.2 The delta method and its applications 183.

Notes:

Includes bibliographical references and index.

ISBN:

047085071X

OCLC:

53460942