Modelling geographically referenced survival data with a cure fraction
F Cooner, S Banerjee… - Statistical methods in …, 2006 - journals.sagepub.com
The emergence of geographical information systems and related softwares nowadays
enables medical databases to incorporate the geographical information on patients …
enables medical databases to incorporate the geographical information on patients …
Semiparametric proportional odds models for spatially correlated survival data
S Banerjee, DK Dey - Lifetime data analysis, 2005 - Springer
The last decade has witnessed major developments in Geographical Information Systems
(GIS) technology resulting in the need for statisticians to develop models that account for …
(GIS) technology resulting in the need for statisticians to develop models that account for …
Modelling spatially correlated survival data for individuals with multiple cancers
U Diva, S Banerjee, DK Dey - Statistical modelling, 2007 - journals.sagepub.com
Epidemiologists and biostatisticians investigating spatial variation in diseases are often
interested in estimating spatial effects in survival data, where patients are monitored until …
interested in estimating spatial effects in survival data, where patients are monitored until …
spatsurv: an R package for Bayesian inference with spatial survival models
BM Taylor, BS Rowlingson - Journal of Statistical Software, 2017 - jstatsoft.org
Survival methods are used for the statistical modelling of time-to-event data. Survival data
are characterized by a set of complete records, in which the time of the event is known; and …
are characterized by a set of complete records, in which the time of the event is known; and …
Parametric models for spatially correlated survival data for individuals with multiple cancers
U Diva, DK Dey, S Banerjee - Statistics in medicine, 2008 - Wiley Online Library
Incorporating spatial variation could potentially enhance information coming from survival
data. In addition, simultaneous (joint) modeling of time‐to‐event data from different …
data. In addition, simultaneous (joint) modeling of time‐to‐event data from different …
Bayesian modelling of spatial heterogeneity in disease maps with application to German cancer mortality data
L Knorr-Held, N Becker - 1999 - epub.ub.uni-muenchen.de
This paper starts with a short overview of basic concepts in disease mapping such as
relative risk and age-standardization. Then two recent methods for advanced statistical …
relative risk and age-standardization. Then two recent methods for advanced statistical …
A transformation class for spatio-temporal survival data with a cure fraction
SM Hurtado Rúa, DK Dey - Statistical methods in medical …, 2016 - journals.sagepub.com
We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal
clustered survival data with possibility of cure. A flexible continuous transformation class of …
clustered survival data with possibility of cure. A flexible continuous transformation class of …
Generalized accelerated failure time spatial frailty model for arbitrarily censored data
Flexible incorporation of both geographical patterning and risk effects in cancer survival
models is becoming increasingly important, due in part to the recent availability of large …
models is becoming increasingly important, due in part to the recent availability of large …
Reliability-adjusted disease maps
S Kennedy-Kalafatis - Social Science & Medicine, 1995 - Elsevier
Bayesian methods for adjusting mortality and morbidity rates to account for variations
caused by small numbers are presented. Although such methods produce statistically …
caused by small numbers are presented. Although such methods produce statistically …
spBayesSurv: Fitting Bayesian spatial survival models using R
Spatial survival analysis has received a great deal of attention over the last 20 years due to
the important role that geographical information can play in predicting survival. This paper …
the important role that geographical information can play in predicting survival. This paper …