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Lawson A.B., Browne W.J., Rodeiro C.L. — Disease Mapping with WinBUGS and MLwiN
Lawson A.B., Browne W.J., Rodeiro C.L. — Disease Mapping with WinBUGS and MLwiN

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Название: Disease Mapping with WinBUGS and MLwiN

Авторы: Lawson A.B., Browne W.J., Rodeiro C.L.

Аннотация:

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages – such as WinBUGS and MLwiN – are now easy to implement in practice. Provides an introduction to Bayesian and multilevel modelling in disease mapping. Adopts a practical approach, with many detailed worked examples. Includes introductory material on WinBUGS and MLwiN. Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis. Suitable for public health workers and epidemiologists with a sound statistical knowledge. Supported by a Website featuring data sets and WinBUGS and MLwiN programs. Disease Mapping with WinBUGS and MLwiN provides a practical introduction to the use of software for disease mapping for researchers, practitioners and graduate students from statistics, public health and epidemiology who analyse disease incidence data.


Язык: en

Рубрика: Математика/Вероятность/Статистика и приложения/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2003

Количество страниц: 282

Добавлена в каталог: 04.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Adaptive rejection sampling      24 41 47 96—97
At risk background      4
Autocorrelation function ACF      99
BACC      23
Bayes estimate      11
Bayes factor      26
Bayesian information criterion      26
Bayesian residual      27
Block kriging      210
Block updates      23
Boa      66
Bootstrapping      75
Brooks — Draper diagnostic      25 99
BYM model      123 125
Case control      7
Case-control design      158
Case-event analysis      2
Census tracts      2
Cluster detection      1
Coda      63 66
compound documents      48
Conditional autoregressive models, CAR      43 76 111 123 222
Conditional autoregressive models, car.I1      70
Conditional autoregressive models, car.normal      70
Conditional autoregressive models, car.proper      70 124
Conditional predictive ordinates      28
Confounder variables      6 7
Constant nodes      51
Control disease      158
Convergence      66
Convolution model      111
Correlated heterogeneity      10
Correlated heterogeneity, CH      167
Counties      2
Cross-validation      208
Cusum methods      2 5
DAG, directed acyclic graph      19
Dataset, East German lip cancer, 1980—1989      207
Dataset, European melanoma mortality, 1971—1980      77
Dataset, Falkirk respiratory cancer, 1978—1983      167 190—191
Dataset, Ohio respiratory cancer mortality, 1979—1988      116 128 180
Dataset, owa cancer registry survival data      235
Dataset, Scottish lip cancer      105
Dataset, South Carolina cancer mortality, 1998      69
Dataset, South Carolina congenital abnormality deaths      5 116 213
Dataset, South Carolina low birth weight, 2000      203 223
Dataset, South Carolina malignant neoplasm mortality, 1999      116 199 220
Dataset, total deaths in England and Wales      31
Deprivation indices      7
Deviance      62
DIC diagnostic      38 100 126 1 227 233
DIC diagnostic, deviance information criterion      26 47
Diffuse prior distributions      3 7
Disease clustering      1
Disease mapping      1
Doodlebugs      49 59
Ecological analysis      1 160
Ecological bias      197
Ecological fallacy      165
Ecological regression studies      199
EDA methods      6
Edge effects      251
EM algorithm      36
Empirical Bayes      11
Excel      77
Exposure modelling      160
External standardization      7
Extra binomial variation      227
Frailty      9 181
Frequentist approach      10
Full Bayes      11
Gauss — Hermite quadrature      15 39
Gaussian kriging models      71
Gelman — Rubin diagnostic      119 122 124 132 199
Gelman — Rubin statistic      25 63 130
Generalized additive models      6
Generalized linear mixed models      45
GeoBUGS      67
Geographically weighted regression GWR      207 232
Gibbs sampling      13 45
Gibbs Updates      23 96
Gibbs — Metropolis sampling      14
GIS, geographical information systems      xvii
Glm function      9
GLS estimation      36
Graphical models      51
Hidden process models      252
Hierarchical models      18
HLM package      30 37
Hybrid Metropolis — Gibbs algorithm      41
Hyperparameters      123
Hyperprior distribution      18 123
Intra-class correlation      31
Inverse Wishart prior distribution      152
Iterative generalized least squares estimation, IGLSE      36 109
Kernel regression      6
Laplace approximation      40
Laplace asymptotic integral approximation      13
Likelihood models      6
Linear Bayes methods      13
Log-concave posterior      24
Log-linear modelling      9
Log-normal model      120
Logical nodes      51
Map surveillance      252
Marginal likelihood      11
Marginal maximum likelihood      11
Marginal quasi-likelihood (MOL) algorithm      40
Markov chain      20—21
Markov chain Monte Carlo      27 46 94
Maximum a posteriori estimation      12 20
MCMC convergence      25
MCMC diagnostics      104
Metropolis updates      22 96
Metropolis — Hastings algorithm      14 21—22
Metropolis — Hastings updates      22
Mixture model      133
MLwiN macros      1 50
MLwiN worksheet      77
MOL estimation      87 90 107 146
Moran's I statistic      27
Multiple comparisons      158
Multiple-membership models      15 42 106 222
Multiple-membership multiple-classification models MMMC      43
Multiplicative expected risk      4
Multivariate normal distribution      3 6
Multivariate, CAR models      252
Multivariate, disease mapping      251
Nearest neighbour sets      216
Nonparametric maximum likelihood      13
Nonspecific heterogeneity      10
Overdispersion      9
Parametric bootstrap      2 7
Partial autocorrelation function, PACF      99
Partition models      6
Point process models      2 252
Poisson distribution      7
Poisson process models      6 252
Poisson regression      8 85—86 101
Poisson-gamma model      11 117 118
POL algorithm      40 90 97 108
Post code      2
Post hoc analysis      158
Posterior approximation      11
Posterior distribution      11 17
Posterior expectation      11
Posterior inference      19
Posterior predictive distribution      28
Posterior sampling      12
Prior distributions      17
Prospective study      156
Public health surveillance      1
Putative source of hazard      1
Quantile-quantile plots      25
Quasi-likelihood estimates      40
Quasi-likelihood methods      43 98 231
Raftery — Lewis diagnostic      25 99
Random coefficient model      33
Random effects      9 11
Random intercepts model      33
Random slopes model      33
Random walk      181
Rectangular format      5 7
Relative risk      1 4 8
Restricted iterative generalized least squares, RIGLS      36
Restricted maximum likelihood, REML      36 75
Retrospective study      156
S-Plus format      57
Saturated estimate      5
Saturated ML estimator      7
Scripts      64
Sequential Monte Carlo estimation      252
Simple kriging      214
Slice sampling      24
Space-time interaction      185
Space-time models      128
Sparseness      9
Spatial autocorrelation      10 15
Spatial prediction      137
Spatial survival analysis      235
Spatial trend      7
Specific heterogeneity      10
Standardized mortality/morbidity ratio, SMR      5 31 116
Standardized mortality/morbidity ratio, variance      5
Stochastic nodes      51
Tract centroid      2 4
Tract count analysis      2
Uncorrelated heterogeneity, UH      10 167
Univariate random walk Metropolis sampling      41
Unobserved heterogeneity      162
Uranium field      213
VARCL      30 36
Variance components model      31
zip code      2
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