Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model

G Onicescu, A Lawson, J Zhang… - … methods in medical …, 2017 - journals.sagepub.com
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …
被引用次数：18 相关文章

Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model.

G Onicescu, A Lawson, J Zhang… - Statistical Methods in …, 2015 - europepmc.org
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …
[PDF] researchgate.net

[PDF][PDF] Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model

G Onicescu, A Lawson, J Zhang… - Stat Methods Med …, 2017 - researchgate.net
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …

Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model

G Onicescu, A Lawson, J Zhang… - Statistical methods …, 2017 - pubmed.ncbi.nlm.nih.gov
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …

Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model

G Onicescu, A Lawson, J Zhang… - Statistical …, 2017 - researchdiscovery.drexel.edu
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …
[HTML] nih.gov

[HTML][HTML] Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model

G Onicescu, A Lawson, J Zhang… - Statistical methods in …, 2017 - ncbi.nlm.nih.gov
In this paper, we extend the spatially explicit survival model for small area cancer data by
allowing dependency between space and time and using accelerated failure time models …