Grant Details

Grant Number: |
5R01CA112444-03 Interpret this number |

Primary Investigator: |
Banerjee, Sudipto |

Organization: |
University Of Minnesota |

Project Title: |
Hierachial Modeling Approaches for Geographical Boundary Analysis in Cancer Studi |

Fiscal Year: |
2008 |

Abstract

Boundary analysis concerns the detection and analysis of zones of abrupt change in spatial maps. Its importance in understanding scientific phenomena has been widely recognized in fields such as genetics and ecology. However, current methods are based upon rather ad-hoc deterministic algorithms. This project intends to develop formal statistical methods for carrying out boundary analysis, exploiting modern GIS tools to advance the development and interpretation of boundary analysis in spatial (cancer-related) maps. Attendant benefits of the project will include enhancements in the understanding of spatial structure associated with information displayed in cancer-related maps. Goals of this project include development of boundary analysis from an inferential perspective with evaluation of statistical modeling approaches using cancer data from the Minnesota Cancer Surveillance System (MCSS), the Iowa Women's Health Survey (IWHS), the Surveillance Epidemiology and End Results (SEER) (http://seer.cancer.gov) database of the National Cancer Institute, as well as Medicare usage and cancer hospice mortality data. Applications for environmental risk factor data from the Environmental Protection Agency (EPA) will also be carried out to draw toxin boundaries that may reveal interesting cancer-toxin relationships.

Publications

**Modelling Geographically Referenced Survival Data With A Cure Fraction**

**Authors:**Cooner,F. , Banerjee,S. , McBean,A.M. .

**Source:**Statistical Methods In Medical Research, 2006 Aug; 15(4), p. 307-24.

**PMID:**16886733

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**Parametric Models For Spatially Correlated Survival Data For Individuals With Multiple Cancers**

**Authors:**Diva,U. , Dey,D.K. , Banerjee,S. .

**Source:**Statistics In Medicine, 2008-05-30 00:00:00.0; 27(12), p. 2127-44.

**PMID:**18167633

Related Citations

**Hierarchical Spatial Modeling Of Additive And Dominance Genetic Variance For Large Spatial Trial Datasets**

**Authors:**Finley,A.O. , Banerjee,S. , Waldmann,P. , Ericsson,T. .

**Source:**Biometrics, 2009 Jun; 65(2), p. 441-51.

**PMID:**18759829

Related Citations

**Bayesian Wombling For Spatial Point Processes**

**Authors:**Liang S. , Banerjee S. , Carlin B.P. .

**Source:**Biometrics, 2009 Dec; 65(4), p. 1243-53.

**PMID:**19302408

Related Citations

**Bayesian Modeling Of Exposure And Airflow Using Two-zone Models**

**Authors:**Zhang,Y. , Banerjee,S. , Yang,R. , Lungu,C. , Ramachandran,G. .

**Source:**The Annals Of Occupational Hygiene, 2009 Jun; 53(4), p. 409-24.

**PMID:**19403840

Related Citations

**Hierarchical And Joint Site-edge Methods For Medicare Hospice Service Region Boundary Analysis**

**Authors:**Ma H. , Carlin B.P. , Banerjee S. .

**Source:**Biometrics, 2010 Jun; 66(2), p. 355-64.

**PMID:**19645704

Related Citations

**Gaussian Predictive Process Models For Large Spatial Data Sets**

**Authors:**Banerjee S. , Gelfand A.E. , Finley A.O. , Sang H. .

**Source:**Journal Of The Royal Statistical Society. Series B, Statistical Methodology, 2008-09-01 00:00:00.0; 70(4), p. 825-848.

**PMID:**19750209

Related Citations

**Modelling Spatially Correlated Survival Data For Individuals With Multiple Cancers**

**Authors:**Diva U. , Banerjee S. , Dey D.K. .

**Source:**Statistical Modelling, 2007-07-01 00:00:00.0; 7(2), p. 191-213.

**PMID:**19789726

Related Citations

**Bayesian Wombling: Curvilinear Gradient Assessment Under Spatial Process Models**

**Authors:**Banerjee S. , Gelfand A.E. .

**Source:**Journal Of The American Statistical Association, 2006-12-01 00:00:00.0; 101(476), p. 1487-1501.

**PMID:**20221318

Related Citations

**Hierarchical Spatial Models For Predicting Tree Species Assemblages Across Large Domains**

**Authors:**Finley A.O. , Banerjee S. , McRoberts R.E. .

**Source:**The Annals Of Applied Statistics, 2009-09-01 00:00:00.0; 3(3), p. 1052-1079.

**PMID:**20352037

Related Citations

**Smoothed Anova With Spatial Effects As A Competitor To Mcar In Multivariate Spatial Smoothing**

**Authors:**Zhang Y. , Hodges J.S. , Banerjee S. .

**Source:**The Annals Of Applied Statistics, 2009; 3(4), p. 1805-1830.

**PMID:**20596299

Related Citations

**Hierarchical Spatial Process Models For Multiple Traits In Large Genetic Trials**

**Authors:**Banerjee S. , Finley A.O. , Waldmann P. , Ericsson T. .

**Source:**Journal Of The American Statistical Association, 2010-06-01 00:00:00.0; 105(490), p. 506-521.

**PMID:**20676229

Related Citations

**Order-free Co-regionalized Areal Data Models With Application To Multiple-disease Mapping**

**Authors:**Jin X. , Banerjee S. , Carlin B.P. .

**Source:**Journal Of The Royal Statistical Society. Series B, Statistical Methodology, 2007-11-01 00:00:00.0; 69(5), p. 817-838.

**PMID:**20981244

Related Citations

**Flexible Cure Rate Modeling Under Latent Activation Schemes**

**Authors:**Cooner F. , Banerjee S. , Carlin B.P. , Sinha D. .

**Source:**Journal Of The American Statistical Association, 2007-06-01 00:00:00.0; 102(478), p. 560-572.

**PMID:**21031152

Related Citations

**Spbayes: An R Package For Univariate And Multivariate Hierarchical Point-referenced Spatial Models**

**Authors:**Finley A.O. , Banerjee S. , Carlin B.P. .

**Source:**Journal Of Statistical Software, 2007 Apr; 19(4), p. 1-24.

**PMID:**21494410

Related Citations

**Mining Boundary Effects In Areally Referenced Spatial Data Using The Bayesian Information Criterion**

**Authors:**Li P. , Banerjee S. , McBean A.M. .

**Source:**Geoinformatica, 2011 Jul; 15(3), p. 435-454.

**PMID:**21643463

Related Citations

**A Hierarchical Model For Quantifying Forest Variables Over Large Heterogeneous Landscapes With Uncertain Forest Areas**

**Authors:**Finley A.O. , Banerjee S. , MacFarlane D.W. .

**Source:**Journal Of The American Statistical Association, 2011; 106(493), p. 31-48.

**PMID:**26139950

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