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Detection of spatial variations in temporal trends with a quadratic function

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Detection of spatial variations in temporal trends with a quadratic function. / Moraga-Serrano, Paula Esther; Kulldorff, Martin.
In: Statistical Methods in Medical Research, Vol. 25, No. 4, 2016, p. 1422-1437.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Moraga-Serrano, PE & Kulldorff, M 2016, 'Detection of spatial variations in temporal trends with a quadratic function', Statistical Methods in Medical Research, vol. 25, no. 4, pp. 1422-1437. https://doi.org/10.1177/0962280213485312

APA

Moraga-Serrano, P. E., & Kulldorff, M. (2016). Detection of spatial variations in temporal trends with a quadratic function. Statistical Methods in Medical Research, 25(4), 1422-1437. https://doi.org/10.1177/0962280213485312

Vancouver

Moraga-Serrano PE, Kulldorff M. Detection of spatial variations in temporal trends with a quadratic function. Statistical Methods in Medical Research. 2016;25(4):1422-1437. Epub 2013 Apr 23. doi: 10.1177/0962280213485312

Author

Moraga-Serrano, Paula Esther ; Kulldorff, Martin. / Detection of spatial variations in temporal trends with a quadratic function. In: Statistical Methods in Medical Research. 2016 ; Vol. 25, No. 4. pp. 1422-1437.

Bibtex

@article{fdcc9c8ee44e472cbd0b8fb370c451ed,
title = "Detection of spatial variations in temporal trends with a quadratic function",
abstract = "Methods for the assessment of spatial variations in temporal trends (SVTT) are important tools for disease surveillance, which can help governments to formulate programs to prevent diseases, and measure the progress, impact, and efficacy of preventive efforts already in operation. The linear SVTT method is designed to detect areas with unusual different disease linear trends. In some situations, however, its estimation trend procedure can lead to wrong conclusions. In this article, the quadratic SVTT method is proposed as alternative of the linear SVTT method. The quadratic method provides better estimates of the real trends, and increases the power of detection in situations where the linear SVTT method fails. A performance comparison between the linear and quadratic methods is provided to help illustrate their respective properties. The quadratic method is applied to detect unusual different cervical cancer trends in white women in the United States, over the period 1969 to 1995.",
author = "Moraga-Serrano, {Paula Esther} and Martin Kulldorff",
year = "2016",
doi = "10.1177/0962280213485312",
language = "English",
volume = "25",
pages = "1422--1437",
journal = "Statistical Methods in Medical Research",
issn = "0962-2802",
publisher = "SAGE Publications Ltd",
number = "4",

}

RIS

TY - JOUR

T1 - Detection of spatial variations in temporal trends with a quadratic function

AU - Moraga-Serrano, Paula Esther

AU - Kulldorff, Martin

PY - 2016

Y1 - 2016

N2 - Methods for the assessment of spatial variations in temporal trends (SVTT) are important tools for disease surveillance, which can help governments to formulate programs to prevent diseases, and measure the progress, impact, and efficacy of preventive efforts already in operation. The linear SVTT method is designed to detect areas with unusual different disease linear trends. In some situations, however, its estimation trend procedure can lead to wrong conclusions. In this article, the quadratic SVTT method is proposed as alternative of the linear SVTT method. The quadratic method provides better estimates of the real trends, and increases the power of detection in situations where the linear SVTT method fails. A performance comparison between the linear and quadratic methods is provided to help illustrate their respective properties. The quadratic method is applied to detect unusual different cervical cancer trends in white women in the United States, over the period 1969 to 1995.

AB - Methods for the assessment of spatial variations in temporal trends (SVTT) are important tools for disease surveillance, which can help governments to formulate programs to prevent diseases, and measure the progress, impact, and efficacy of preventive efforts already in operation. The linear SVTT method is designed to detect areas with unusual different disease linear trends. In some situations, however, its estimation trend procedure can lead to wrong conclusions. In this article, the quadratic SVTT method is proposed as alternative of the linear SVTT method. The quadratic method provides better estimates of the real trends, and increases the power of detection in situations where the linear SVTT method fails. A performance comparison between the linear and quadratic methods is provided to help illustrate their respective properties. The quadratic method is applied to detect unusual different cervical cancer trends in white women in the United States, over the period 1969 to 1995.

U2 - 10.1177/0962280213485312

DO - 10.1177/0962280213485312

M3 - Journal article

VL - 25

SP - 1422

EP - 1437

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 4

ER -