Spatial data analysis

S Banerjee - Annual review of public health, 2016 - annualreviews.org
With increasing accessibility to geographic information systems (GIS) software, statisticians
and data analysts routinely encounter scientific data sets with geocoded locations. This has …

A Bayesian normal mixture accelerated failure time spatial model and its application to prostate cancer

S Wang, J Zhang, AB Lawson - Statistical methods in …, 2016 - journals.sagepub.com
In the United States, prostate cancer is the third most common cause of death from cancer in
males of all ages, and the most common cause of death from cancer in males over age 75. It …

Spatial survival models

S Banerjee - … of Modern Statistical Methods. Handbook of …, 2016 - api.taylorfrancis.com
Epidemiological and biomedical studies often require modeling and analysis for time-
toevent data, where a subject is followed up to an event (eg, death or onset of a disease) or …

Kernel estimation of hazard functions when observations have dependent and common covariates

JL Wolter - Journal of econometrics, 2016 - Elsevier
We propose a hazard model where dependence between events is achieved by assuming
dependence between covariates. This model allows for correlated variables specific to …

[PDF][PDF] Modeling Time to First Malaria Using Spatially Correlated Conditional Autoregressive Frailty Model

S Wondaya, YG Kifle, AB Tereda, D Seyoum - 2016 - researchgate.net
Introduction: The burden of malaria is a major public health concern in Ethiopia. Its dynamics
is being changed by construction of dams which serve either for hydroelectric or irrigation …

[PDF][PDF] Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation …

M Rostamiforooshani - 2016 - harvest.usask.ca
In practice, survival data are often grouped into clusters, such as clinical sites, geographical
regions and so on. This clustering imposes correlation among individuals within each …