Veterinary Epidemiologic Research

727 Pages·2003·25.74 MB·English

by  Ian Dohoo

VETER1NA.RY
EP1DEMl OLOGl C
RESEARCH
lan Dohoo Wayne Martin Henrik Stryhn
VETERINARY
EPIDEMIOLOGIC
RESEARCH
VETERINARY
EPIDEMIOLOGIC
RESEARCH
lan Dohoo
Professor of Epidemiology
Department of HeaIth Management
University of Prince Edward Island
Charlottetown Prince Edward Island Canada
Wayne Martin
Professor of Epidemiology
Department of Population Medicine
University of Guelph
Guelph Ontario Canada
Henrik Stryhn
Associate Professor of Biostatistics
Department of HeaIth Management
University ofPrince Edward Island
Charlottetown Prince Edward Island Canada
EditorlProofreader/Compositor/Publication coordinator: S Margaret McPike
Cover designer: Gregory Mercier
Printer: Transcontinental Prince Edward Island
© 2003, by AVC Inc. Ali rights reserved. This book is protected by copyright. No part of this book may be
reproduced, stored in a retrieval system or transmitted, in any form or by any means - electronic, mechanical,
photocopy, recording, or otherwise - without the written permission of the publisher. For information write:
AVC Inc., University of Prince Edward Island, 550 University Avenue, Charlottetown, Prince Edward
Island, Canada, CIA 4P3
Printed in Canada
10987654321
National Library of Canada Cataloguing in Publication
Veterinary epidemiologic research / lan Dohoo ... [et al.].
IncJudes index.
ISBN 0-919013-41-4
I. Veterinary epidemiology--Research--Textbooks.
I. Dohoo, lan Robert
SF780.9.V472003 636.089'44 C2003-9045 18-8
Care has been taken to confirm the accuracy of the information presented. Nevertheless, the authors,
editors, and publisher are not responsible for errors or omissions or for any consequences from application
of the information in this book and make no warranty, express or implied, with respect to the content ofthe
publication.
Dedication
This text is dedicated to ali of the graduate students who have
challenged and inspired us throughout our careers,
and to our families who have supported us,
especially during the writing of this text

CONTENTS
Foreword xv
Preface xvi
Reference list xviii
Acknowledgements XIX
l. INTRODUCTION AND CAUSAL CONCEPTS 1
1.1 Introduction 2
1.2 A brief history of multiple causation concepts 2
1.3 A brief history of scientific inference 5
lA Key components of epidemiologic research 8
1.5 Seeking causes 10
1.6 Models of causation 12
1.7 Component-cause model l3
1.8 Causal-web model 18
1.9 Constructing a causal diagram 19
1.10 Causal criteria 21
2. SAMPLlNG 27
2.1 Introduction 28
2.2 Non-probability sampling 30
2.3 Probability sampling 31
2.4 Simple random sample 32
2.5 Systematic random sample 32
2.6 Stratified random sample 32
2.7 Cluster sampling 33
2.8 Multistage sampling 34
2.9 Analysis of survey data 35
2.l0 Sample-size determination 39
2.11 Sampling to detect disease 47
3. QUESTIONNAIRE DESIGN 53
3.1 Introduction 54
3.2 Designing the question 56
3.3 Open question 57
304 Closed question 57
3.5 Wording the question 60
3.6 Structure of questionnaire 61
3.7 Pre-testing questionnaires 62
3.8 Data coding and editing 63
viii CONTENTS
4. MEASURES OF DISEASE FREQUENCY 65
4.1 Introduction 66
4.2 Count, proportion, odds and rate 66
4.3 Incidence 67
4.4 Ca1cu1ating risk 68
4.5 Ca1cu1ating incidence rate s 70
4.6 Relationship between risk and rate 71
4.7 Prevalence 72
4.8 Mortality statistics 73
4.9 Other measures of disease frequency 75
4.10 Confidence intervals 75
4.ll Standardisation of risks and rates 76
4.12 Application 81
5. SCREENING AND DIAGNOSTIC TESTS 85
5.1 Introduction 86
5.2 Laboratory-based concepts 86
5.3 The abi1ity of a test to detect disease or health 93
5.4 Estimating test sensitivity and specificity 96
5.5 Predictive values 99
5.6 Using multiple tests 101
5.7 Estimating the true prevalence of disease 109
5.8 Sensitivity and specificity estimations using logistic regression 109
5.9 Estimating Se and Sp without a gold standard 111
5.10 Herd-level testing 113
6. MEASURES OF ASSOCIATION 121
6.1 Introduction 122
6.2 Measures of association 123
6.3 Measures of effect 126
6.4 Hypothesis testing and confidence intervals 131
7. INTRODUCTION TO OBSERVATIONAL STUDIES 139
7.1 Introduction 140
7.2 Descriptive studies 142
7.3 Observational analytic (explanatory) studies 143
7.4 Cross-sectional studies 144
7.5 Examples of cross-sectional studies 146
8. COHORT STUDIES 151
8.1 Introduction 152
8.2 Basis 152
CONTENTS ix
8.3 The exposure 153
8.4 Sample-size aspects 156
8.5 The nature of the exposure groups 156
8.6 Ensuring exposed and non-exposed group s are comparable 158
8.7 Follow-up period and processes 159
8.8 Measuring the outcome 159
8.9 Analysis/interpretation 160
9. CASE-CONTROL STUDIES 163
9.1 Introduction 164
9.2 The study bas e 164
9.3 The case series 165
9.4 Principles of control selection 167
9.5 Selecting controls in risk-based designs 167
9.6 Selecting controls in rate-based designs 169
9.7 Other sources of contro1s 172
9.8 The issue of 'representativeness' 173
9.9 More than one control group 174
9.10 More than one control per case 174
9.11 Analysis of case-control data 174
10. HYBRID STUDY DESIGNS 177
10.1 Introduction 178
10.2 Case-cohort studies 178
10.3 Case-crossover studies 180
10.4 Case-only studi es 181
10.5 Two-stage sampling designs 182
11. CONTROLLED TRIALS 185
11.1 Introduction 186
11.2 Stating the objectives 189
11.3 The study population 190
11.4 Allocation of participants 193
11.5 Specifying the intervention 197
11.6 Masking (blinding) 198
11.7 F ollow-up/comp1iance 198
11.8 Measuring the outcome 200
11.9 Analysis 200
11.10 Ethical considerations 203
12. VALIDITY IN OBSERVATIONAL STUDIES 207
12.1 Introduction 208
x CONTENTS
12.2 Selection bias 208
12.3 Examples ofselection bias 212
12.4 Reducing selection bias 217
12.5 Information bias 219
12.6 Bias from misclassification 220
12.7 Misclassification ofmultinomial exposure or disease categories 228
12.8 Validation studies to correct misclassification 228
12.9 Measurement error 229
12.10 Measurement error in surrogate measures of exposure 231
12.11 Misclassification and measurement errors - impact on sample size 232
13. CONFOUNDER BlAS: ANALYTIC CONTROL
AND MATCHING 235
13.1 Introduction 236
13.2 Confounding and causation 236
13.3 What extraneous factors are confounders? 237
13.4 Criteria for confounding 239
13.5 Control of confounding 239
13.6 Matching 240
13.7 Analytic control of confounding 245
13.8 Stratified analysis to control confounding 250
13.9 Stratified analysis when interaction is present 253
13.10 Extemal adjustment of odds ratios for unmeasured confounders 258
13.11 Multivariable causation and data analyses 259
13.12 Summary of effects of extraneous variables 270
14. LINEAR REGRESSION 273
14.1 Introduction 274
14.2 Regression analysis 274
14.3 Hypothesis testing and effect estimation 276
14.4 Nature of the X-variables 284
14.5 Modeling highly correlated (collinear) variables 289
14.6 Detecting and modeling interaction 291
14.7 Causal interpretation of a multivariable linear model 294
14.8 Evaluating the least squares model 294
14.9 Evaluating the major assumptions 301
14.10 Assessment of each observation 307
14.11 Comments on the model deficiencies 312
15. MODEL-BUILDING STRATEGIES 317
15.1 Introduction 318