Statistical methods in environmental epidemiology:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Oxford [u.a.]
Oxford University Press
2009
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references (p. [368]-425) and index |
| Beschreibung: | xv, 432 p. graph. Darst. 24 cm |
| ISBN: | 9780199232895 019923289X 9780199232901 0199232903 |
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| 100 | 1 | |a Thomas, Duncan C. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Statistical methods in environmental epidemiology |c Duncan C. Thomas |
| 250 | |a 1. publ. | ||
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| 300 | |a xv, 432 p. |b graph. Darst. |c 24 cm | ||
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| 500 | |a Includes bibliographical references (p. [368]-425) and index | ||
| 650 | 4 | |a Environmentally induced diseases |x Epidemiology |x Statistical methods | |
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Datensatz im Suchindex
| _version_ | 1804140931628138496 |
|---|---|
| adam_text | Titel: Statistical methods in environmental epidemiology
Autor: Thomas, Duncan C.
Jahr: 2009
Contents
Preface xiv
1 A tale of two exposures 1
The ionizing radiation tale 3
The air pollution tale 11
2 Basic epidemiologic study designs 19
Experimental 19
Descriptive 20
Geographic comparisons 20
Temporal comparisons 21
Prevalence surveys 21
Analytical 22
Cohort study design 23
Case-control study design 24
Nested case-control and case-cohort designs 28
Interpretation of epidemiologic associations 29
3 Basic statistical methods 33
Basic probability theory 33
Probability distributions used in epidemiology 36
Binomial distribution 36
Poisson distribution 36
Normal distribution 38
Chi square distribution 38
Measures of disease frequency and risk 39
Absolute risk 40
Risk 40
Rates 41
Survival analysis 41
Relative risk 43
Case-control studies 45
iji Contents
48
Cohort studies
Attributable risk and other measures of ^
public health impact ^
Interaction 52
Basic principles of statistical inference
— 55
4 Multivariate models _____——
__^__«--«««-—--«---— — -— — ^
Linear regression for continuous data
Multivariate models for binary data ^
Logistic regression ^
Binomial regression for grouped binary data ^
Censored survival analysis ,g
Nested case-control studies _q
Poisson regression _j
Extra-Poisson variation 72
Principles of ML inference oq
Bayesian methods g2
The general linear model g2
Generalized estimating equations 5
Missing data R,
Missingness models _
Missing data imputation _
Missing indicator methods
92
5 Some special-purpose designs
92
Two-phase case-control designs
Counter-matching
in3
Case-distribution studies
104
Case-crossover design
Poisson process model for recurrent events
Case-specular design *
Case-only and case-parent-triad designs 1
6 Modeling exposure-time-response relationships 11 °
Basic dose-response models ^ ®
Parametric models 111
Nonparametric models 1^5
Incorporating temporal modifiers ^ ^4
Extended exposure histories 12^
Contents ix
Modeling temporal modifiers for tobacco smoking 133
Modeling short-term fluctuations in exposure 137
Dose heterogeneity 138
7 Longitudinal models 139
Continuous outcomes 140
Single observations 140
Paired observations 142
Repeated measurements 144
Binary and categorical outcomes: General
linear mixed models 149
Combined longitudinal and survival outcomes 150
Panel studies 151
Missing longitudinal data 154
8 Time-series models
for acute effects 158
Methods for a single time series 159
Distributed lag models 164
The harvesting hypothesis 165
Multiple time series 168
Time series for individual data 171
Comparing acute and chronic effect estimates 172
9 Spatial models 176
Mapping exposures and disease 178
Continuous spatial data 178
Designing a measurement network 184
Poisson count data 185
Individual case-control data 189
Spatial correlations of exposure and disease 189
Tests of correlation with a single point source 189
Tests of association with spatially defined exposures 190
Case clustering and surveillance 193
Tests of clustering behavior 193
Space-time clustering 195
Evaluation of specific clusters 196
Geographic information systems 198
x Contents
__»«_-»_----------------- —— • 2Q2
10 Ecologic inference _____-_~-~-~--~ -~—-
———~-—-—-—-—---——¦¦¦-•- ~™ ~~ 204
Hybrid aggregate/individual designs 2Q6
Ecologic bias 206
Linear models 208
Models for disease rates 21 o
Examples 210
Domestic radon and lung cancer 214
Air pollution 216
Latent variable models 217
Multilevel designs
221
11 Measurement error and exposure models ^^^mm^-^-~-----
—-—-—---•—^ 223
A general framework for exposure measurement error
Some other effects of measurement error
Methods of correction for measurement error
Continuous exposure variables ^qi
Parametric regression calibration __
Regression substitution «-«
SIMEX method 32
Parametric likelihood and quasi-Mkelihood methods
Semiparametric efficient estimator method
Bayesian methods _g
Differential measurement error .
Multivariate models
Binary exposure variables
Aggregate, time series, and spatial studies _
Efficient design of validation studies
Some examples of complex dosimetry systems
Dose reconstruction for downwinder studies
247
Nevada Test Site downwinders
Hanford Thyroid Disease Study
Colorado Plateau uranium miners
Use of biodosimetry in the atomic bomb survivors study
Children s Health Study 25
12 Multiple risk factors and interactions 258
Dealing with confounders 2
Selection of confounders, model choice, and model averaging 262
Contents xi
Testing for interactions 267
Multiple exposures, source apportionment,
and complex mixtures 272
Examples of interactions 274
Environment x environment 274
Gene x environment 275
Complex pathways 278
13 Mechanistic models 279
Stochastic models of carcinogenesis 279
Armitage-Doll multistage model 279
Moolgavkar-Knudson two-stage clonal-expansion model 282
Variants incorporating genomic instability and DNA repair 284
Models of bystander effects 289
Microdosimetry models 292
Mechanistic models for noncancer endpoints 295
PBPK models 295
General comments 299
14 Intervention studies 301
Need for Assessment of Public Health Interventions 301
Some natural and planned experiments 304
Government interventions 305
Labor strikes 307
German reunification 307
Olympic games 308
Study designs for program evaluation 308
Randomized experimental designs 308
Individual versus group randomization 310
Staggered intervention design 311
Before-after design with aggregate data (interrupted
time-series study) 312
Before-after design with individual data (panel study) 313
Before-after design with controls 313
Before-during-after design 314
After-only design with controls 315
Routine surveillance 315
Statistical analysis issues 316
VSL versus VSLY approaches 316
Policy issues 317
xii Contents
317
Cost-benefit analysis
The social-political context of intervention research 318
320
15 Risk assessment
321
Risk assessment from epidemiologic data
Estimation of exposure-response relationships
Meta-analysis
Inter-individual variability
Exposure assessment
Risk quantification
Uncertainty analysis
Combination of evidence from different disciplines
337
16 Probability of causation and compensation
338
Causation at the population and individual levels
Attributable risk and probability of causation
Assigned shares for multiple causes
Loss of life expectancy 3
Estimability of PCs and LLEs 345
Schemes for resolving compensation claims
Dealing with uncertainties in compensation 348
17 Further challenges 351
Reproductive endpoints 3^1
Disasters: natural and manmade 3^3
Some examples 354
Tropical cyclones and hurricanes 354
Asian tsunami 355
California and Indonesia fires 356
Bhopal 356
World Trade Center attack 358
Iraq civilian death toll 359
Refugees 359
Chernobyl 360
Global warming 362
Methodological issues 363
Unpredictability 364
Scientific objectives 364
Defining the sampling frame and sampling scheme 364
Contents xiii
Defining the endpoints 365
Assessing exposure-response relationships 365
Global burden of environmental diseases 366
Future challenges 366
References 368
Index 427
|
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| spelling | Thomas, Duncan C. Verfasser aut Statistical methods in environmental epidemiology Duncan C. Thomas 1. publ. Oxford [u.a.] Oxford University Press 2009 xv, 432 p. graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (p. [368]-425) and index Environmentally induced diseases Epidemiology Statistical methods Epidemiologie (DE-588)4015016-1 gnd rswk-swf Biostatistik (DE-588)4729990-3 gnd rswk-swf Umweltkrankheit (DE-588)4131100-0 gnd rswk-swf Umweltkrankheit (DE-588)4131100-0 s Epidemiologie (DE-588)4015016-1 s Biostatistik (DE-588)4729990-3 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018800575&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Thomas, Duncan C. Statistical methods in environmental epidemiology Environmentally induced diseases Epidemiology Statistical methods Epidemiologie (DE-588)4015016-1 gnd Biostatistik (DE-588)4729990-3 gnd Umweltkrankheit (DE-588)4131100-0 gnd |
| subject_GND | (DE-588)4015016-1 (DE-588)4729990-3 (DE-588)4131100-0 |
| title | Statistical methods in environmental epidemiology |
| title_auth | Statistical methods in environmental epidemiology |
| title_exact_search | Statistical methods in environmental epidemiology |
| title_full | Statistical methods in environmental epidemiology Duncan C. Thomas |
| title_fullStr | Statistical methods in environmental epidemiology Duncan C. Thomas |
| title_full_unstemmed | Statistical methods in environmental epidemiology Duncan C. Thomas |
| title_short | Statistical methods in environmental epidemiology |
| title_sort | statistical methods in environmental epidemiology |
| topic | Environmentally induced diseases Epidemiology Statistical methods Epidemiologie (DE-588)4015016-1 gnd Biostatistik (DE-588)4729990-3 gnd Umweltkrankheit (DE-588)4131100-0 gnd |
| topic_facet | Environmentally induced diseases Epidemiology Statistical methods Epidemiologie Biostatistik Umweltkrankheit |
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