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An R package for an integrated evaluation of statistical approaches to cancer incidence projection

Projection of future cancer incidence is an important task in cancer epidemiology. The results are of interest also for biomedical research and public health policy. Age-Period-Cohort (APC) models, usually based on long-term cancer registry data (> 20 yrs), are established for such projections. I...

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Bibliographic Details
Main Authors: Knoll, Maximilian (Author) , Furkel, Jennifer (Author) , Debus, Jürgen (Author) , Abdollahi, Amir (Author) , Karch, André (Author) , Stock, Christian (Author)
Format: Article (Journal)
Language:English
Published: 15 October 2020
In: BMC medical research methodology
Year: 2020, Volume: 20, Pages: 1-11
ISSN:1471-2288
DOI:10.1186/s12874-020-01133-5
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/s12874-020-01133-5
Verlag, lizenzpflichtig, Volltext: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01133-5
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Author Notes:Maximilian Knoll, Jennifer Furkel, Jürgen Debus, Amir Abdollahi, André Karch and Christian Stock
Description
Summary:Projection of future cancer incidence is an important task in cancer epidemiology. The results are of interest also for biomedical research and public health policy. Age-Period-Cohort (APC) models, usually based on long-term cancer registry data (> 20 yrs), are established for such projections. In many countries (including Germany), however, nationwide long-term data are not yet available. General guidance on statistical approaches for projections using rather short-term data is challenging and software to enable researchers to easily compare approaches is lacking.
Item Description:Gesehen am 01.12.2020
Physical Description:Online Resource
ISSN:1471-2288
DOI:10.1186/s12874-020-01133-5

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