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Small Area Disease Risk Estimation and Visualization Using R

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Small Area Disease Risk Estimation and Visualization Using R. / Moraga-Serrano, Paula Esther.
In: The R Journal, Vol. 10, No. 1, 08.2018, p. 495-506.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Moraga-Serrano, PE 2018, 'Small Area Disease Risk Estimation and Visualization Using R', The R Journal, vol. 10, no. 1, pp. 495-506. <https://journal.r-project.org/archive/2018/RJ-2018-036/index.html>

APA

Moraga-Serrano, P. E. (2018). Small Area Disease Risk Estimation and Visualization Using R. The R Journal, 10(1), 495-506. https://journal.r-project.org/archive/2018/RJ-2018-036/index.html

Vancouver

Moraga-Serrano PE. Small Area Disease Risk Estimation and Visualization Using R. The R Journal. 2018 Aug;10(1):495-506. Epub 2018 Jun 7.

Author

Moraga-Serrano, Paula Esther. / Small Area Disease Risk Estimation and Visualization Using R. In: The R Journal. 2018 ; Vol. 10, No. 1. pp. 495-506.

Bibtex

@article{99cee268785c44ec92825dbe2c7d69c8,
title = "Small Area Disease Risk Estimation and Visualization Using R",
abstract = "Small area disease risk estimation is essential for disease prevention and control. In this paper, we demonstrate how R can be used to obtain disease risk estimates and quantify risk factors using areal data. We explain how to define disease risk models and how to perform Bayesian inference using the INLA package. We also show how to make interactive maps of estimates using the leaflet package to better understand the disease spatial patterns and communicate the results. We show an example of lung cancer risk in Pennsylvania, United States, in year 2002, and demonstrate that R represents an excellent tool for disease surveillance by enabling reproducible health data analysis.",
author = "Moraga-Serrano, {Paula Esther}",
year = "2018",
month = aug,
language = "English",
volume = "10",
pages = "495--506",
journal = "The R Journal",
issn = "2073-4859",
publisher = "R Foundation for Statistical Computing",
number = "1",

}

RIS

TY - JOUR

T1 - Small Area Disease Risk Estimation and Visualization Using R

AU - Moraga-Serrano, Paula Esther

PY - 2018/8

Y1 - 2018/8

N2 - Small area disease risk estimation is essential for disease prevention and control. In this paper, we demonstrate how R can be used to obtain disease risk estimates and quantify risk factors using areal data. We explain how to define disease risk models and how to perform Bayesian inference using the INLA package. We also show how to make interactive maps of estimates using the leaflet package to better understand the disease spatial patterns and communicate the results. We show an example of lung cancer risk in Pennsylvania, United States, in year 2002, and demonstrate that R represents an excellent tool for disease surveillance by enabling reproducible health data analysis.

AB - Small area disease risk estimation is essential for disease prevention and control. In this paper, we demonstrate how R can be used to obtain disease risk estimates and quantify risk factors using areal data. We explain how to define disease risk models and how to perform Bayesian inference using the INLA package. We also show how to make interactive maps of estimates using the leaflet package to better understand the disease spatial patterns and communicate the results. We show an example of lung cancer risk in Pennsylvania, United States, in year 2002, and demonstrate that R represents an excellent tool for disease surveillance by enabling reproducible health data analysis.

M3 - Journal article

VL - 10

SP - 495

EP - 506

JO - The R Journal

JF - The R Journal

SN - 2073-4859

IS - 1

ER -