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Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space-time variations in disease incidences. These analyses can provide important information that leads to better decision making in public health. The first part of the book addresses general issues related to epidemiology, GIS, environmental studies, clustering, and ecological analysis. The second part presents basic statistical methods used in spatial epidemiology, including fundamental likelihood principles, Bayesian methods, and testing and nonparametric approaches.
With a focus on special methods, the third part describes geostatistical models, splines, quantile regression, focused clustering, mixtures, multivariate methods, and much more. The final part examines special problems and application areas, such as residential history analysis, segregation, health services research, health surveys, infectious disease, veterinary topics, and health surveillance and clustering. Spatial epidemiology, also known as disease mapping, studies the geographical or spatial distribution of health outcomes.
This handbook offers a wide-ranging overview of state-of-the-art approaches to determine the relationships between health and various risk factors, empowering researchers and policy makers to tackle public health problems.
Recommend to librarian
Andrew B. He has published more than journal articles on spatial epidemiology, spatial statistics, and related areas. Blaveri , Bladder cancer stage and outcome by array-based comparative genomic hybridization , Clinical cancer research , issue. Vert, K. Bleakley, and J. Et-vert , The group fused lasso for multiple change-point detection.
Bouckaert , Probabilistic network construction using the minimum description length principle , Symbolic and quantitative approaches to reasoning and uncertainty , pp.
DOI : Darkhovsky, B. Brodsky, and B. Et-darkhovsky , Nonparametric methods in change point problems , Et-berger-]-casella, G. Et-berger, and R. Et-gupta-]-chen, J. Gupta, and A. Tarsi, D.
Handbook of Spatial Epidemiology - Google книги
Dor, and M. Et-tarsi , A simple algorithm to construct a consistent extension of a partially oriented graph , Efron , Least angle regression. The Annals of statistics , pp. Menezes, P. Eilers, and R. Mckeague, J. Einmahl, and I. Et-mckeague , Empirical likelihood based hypothesis testing , Bernoulli , vol. Et-mackey-fan, Z. Et-mackey, and L. Fearnhead , Exact and efficient Bayesian inference for multiple changepoint problems , Statistics and Computing , vol. Liu, P. Fearnhead, and Z. Friedman , Sparse inverse covariance estimation with the graphical lasso , Biostatistics , vol.
Harchaoui, Z. Hart , Mann-Whitney test is not just a test of medians: differences in spread can be important , BMJ , vol. Hastings , Monte Carlo sampling methods using Markov chains and their applications , Biometrika , vol. Heckerman , Learning bayesian networks : The combination of knowledge and statistical data , Machine learning , vol.
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- Handbook of spatial epidemiology!
Hinkley , Inference about the change-point in a sequence of random variables , Biometrika , vol. James and D. Jandhyala , Inference for single and multiple change-points in time series , Journal of Time Series Analysis , Et-bucy-]-kalman, R. Et-bucy, and R. Fundamentals of Statistical Signal Processing , Asgharian, A.
Recommend to a friend
Khodadadi, and M. Et-asgharian , Changepoint problem and regression: an annotated bibliography , p. Kim, S. Et-cohen, and A. Kruskal, W. Kruskal, and W. Wallis , Use of ranks in onecriterion variance analysis , Journal of the American statistical Association , issue. Leibler, S. Kullback, and R.
Et-leibler , On information and sufficiency. The annals of mathematical statistics , pp. Bacchus, W. Lam, and F. Lauritzen , Graphical models , Et-lebarbier-]-lavielle, M. Et-lebarbier, and E. Et-teyssiere-]-lavielle, M. Et-teyssiere, and G. Lehmann , The power of rank tests. The Annals of Mathematical Statistics , pp.
Lehmann, E. Lehmann, and H. Et-d-'abrera , Nonparametrics: statistical methods based on ranks , Lehmann-et-romano-]-lehmann and J. Et-romano , Testing statistical hypotheses , Leray, P.
Leray, and O. Lichman , UCI machine learning repository , Fong , Homogeneity and change-point detection tests for multivariate data using rank statistics. Mann, H. Mann, and D. Whitney , On a test of whether one of two random variables is stochastically larger than the other. Et-larsen, M. Marx, and R. Et-larsen , Introduction to mathematical statistics and its applications , Matteson and N. Meek , Causal inference and causal explanation with background knowledge , Proceedings of the Eleventh conference on Uncertainty in artificial intelligence , pp.
Related Handbook of Spatial Statistics (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
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