This paper reviews empirical Bayes methods for disease mapping. A distinction is made between spatial models (which take into account the geographical distribution of disease) and nonspatial models. Several estimators are presented, and methods of estimation are described. Empirical Bayes methods are compared with full Bayes methods, and we argue that both have their place
In disease mapping where predictor effects are to be modeled, it is often the case that sets of pred...
Disease mapping methods for the modelling of spatial variation in disease rates, to smooth the extre...
Disease risk varies in space and time due to variation in many factors, including environmental expo...
Abstract: Choropleth maps are frequently used to analyse spatial variations in the risk of a disease...
In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective f...
The analysis of small area disease incidence has now developed to a degree where many methods have b...
Disease maps are effective tools for explaining and predicting patterns of disease outcomes across g...
To compare the occurrence of disease or death in epidemiological or health-policy research an import...
Disease maps are effective tools for explaining and predicting patterns of disease outcomes across g...
This paper starts with a short overview of basic concepts in disease mapping such as relative risk a...
description and analysis of geographically indexed health data with respect to demographic, environm...
Baptista, H., Congdon, P., Mendes, J. M., Rodrigues, A. M., Canhão, H., & Dias, S. S. (2020). Diseas...
Disease maps are geographical maps that display local estimates of disease risk. When the disease is...
This thesis addresses three interrelated challenges of disease mapping and contributes a new approac...
Disease mapping methods for the modeling of spatial variation in disease rates, to smooth the extrem...
In disease mapping where predictor effects are to be modeled, it is often the case that sets of pred...
Disease mapping methods for the modelling of spatial variation in disease rates, to smooth the extre...
Disease risk varies in space and time due to variation in many factors, including environmental expo...
Abstract: Choropleth maps are frequently used to analyse spatial variations in the risk of a disease...
In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective f...
The analysis of small area disease incidence has now developed to a degree where many methods have b...
Disease maps are effective tools for explaining and predicting patterns of disease outcomes across g...
To compare the occurrence of disease or death in epidemiological or health-policy research an import...
Disease maps are effective tools for explaining and predicting patterns of disease outcomes across g...
This paper starts with a short overview of basic concepts in disease mapping such as relative risk a...
description and analysis of geographically indexed health data with respect to demographic, environm...
Baptista, H., Congdon, P., Mendes, J. M., Rodrigues, A. M., Canhão, H., & Dias, S. S. (2020). Diseas...
Disease maps are geographical maps that display local estimates of disease risk. When the disease is...
This thesis addresses three interrelated challenges of disease mapping and contributes a new approac...
Disease mapping methods for the modeling of spatial variation in disease rates, to smooth the extrem...
In disease mapping where predictor effects are to be modeled, it is often the case that sets of pred...
Disease mapping methods for the modelling of spatial variation in disease rates, to smooth the extre...
Disease risk varies in space and time due to variation in many factors, including environmental expo...