Literature DB >> 25558468

Identifying pediatric cancer clusters in Florida using loglinear models and generalized lasso penalties.

Hao Wang1, Abel Rodríguez2.   

Abstract

We discuss the identification of pediatric cancer clusters in Florida between 2000 and 2010 using a penalized generalized linear model. More specifically, we introduce a Poisson model for the observed number of cases on each of Florida's ZIP Code Tabulation Areas (ZCTA) and regularize the associated disease rate estimates using a generalized Lasso penalty. Our analysis suggests the presence of a number of pediatric cancer clusters during the period over study, with the largest ones being located around the cities of Jacksonville, Miami, Cape Coral/Fort Meyers and Palm Beach.

Entities:  

Keywords:  Disease Clustering; Generalized Lasso; Loglinear Models; Pediatric Cancer; Poisson Regression

Year:  2014        PMID： 25558468      PMCID： PMC4280570          DOI： 10.1080/2330443X.2014.960120

Source DB:  PubMed          Journal:  Stat Public Policy (Phila)


  21 in total

1.  Bayesian detection of clusters and discontinuities in disease maps.

Authors:  L Knorr-Held; G Rasser
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  Investigation of excess environmental risk around putative sources: Stone's test with covariate adjustment.

Authors:  T Morton-Jones; P Diggle; P Elliott
Journal:  Stat Med       Date:  1999-01-30       Impact factor: 2.373

3.  Spatial smoothing and hot spot detection for CGH data using the fused lasso.

Authors:  Robert Tibshirani; Pei Wang
Journal:  Biostatistics       Date:  2007-05-18       Impact factor: 5.899

4.  Second-order analysis of spatial clustering for inhomogeneous populations.

Authors:  P J Diggle; A G Chetwynd
Journal:  Biometrics       Date:  1991-09       Impact factor: 2.571

5.  Clustering in linear-mixed models with a group fused lasso penalty.

Authors:  Felix Heinzl; Gerhard Tutz
Journal:  Biom J       Date:  2013-11-18       Impact factor: 2.207

6.  A class of tests for detecting 'general' and 'focused' clustering of rare diseases.

Authors:  T Tango
Journal:  Stat Med       Date:  1995 Nov 15-30       Impact factor: 2.373

7.  Investigations of excess environmental risks around putative sources: statistical problems and a proposed test.

Authors:  R A Stone
Journal:  Stat Med       Date:  1988-06       Impact factor: 2.373

8.  Testing for homogeneity. I. The binomial and multinomial distributions.

Authors:  R F Potthoff; M Whittinghill
Journal:  Biometrika       Date:  1966-06       Impact factor: 2.445

9.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

10.  Epidemiologic mapping of Florida childhood cancer clusters.

Authors:  Raid Amin; Alexander Bohnert; Laurens Holmes; Ayyappan Rajasekaran; Chatchawin Assanasen
Journal:  Pediatr Blood Cancer       Date:  2010-04       Impact factor: 3.167
View more
  3 in total

1.  Simultaneous spatial smoothing and outlier detection using penalized regression, with application to childhood obesity surveillance from electronic health records.

Authors:  Young-Geun Choi; Lawrence P Hanrahan; Derek Norton; Ying-Qi Zhao
Journal:  Biometrics       Date:  2020-12-11       Impact factor: 1.701

2.  An Eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in Khyber-Pakhtunkhwa, Pakistan.

Authors:  Sami Ullah; Hanita Daud; Sarat C Dass; Hadi Fanaee-T; Alamgir Khalil
Journal:  PLoS One       Date:  2018-06-19       Impact factor: 3.240

3.  Lamin A/C Is Dispensable to Mechanical Repression of Adipogenesis.

Authors:  Matthew Goelzer; Amel Dudakovic; Melis Olcum; Buer Sen; Engin Ozcivici; Janet Rubin; Andre J van Wijnen; Gunes Uzer
Journal:  Int J Mol Sci       Date:  2021-06-19       Impact factor: 5.923
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.