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Bayesian approach to cancer-trend analysis using age-stratified Poisson regression models

Pulak Ghosh, Kaushik Ghosh & Ram C Tiwari
Journal Name
Statistics in Medicine
Journal Publication
others
Publication Year
2011
Decision Sciences and Information Systems
Publication Date
Vol. 30, No. 2, PP 127-139, 30 January 2011
Abstract

Annual Percentage Change (APC) summarizes trends in age-adjusted cancer rates over short time-intervals. This measure implicitly assumes linearity of the log-rates over the intervals in question, which may not be valid, especially for relatively longer time-intervals. An alternative is the Average Annual Percentage Change (AAPC), which computes a weighted average of APC values over intervals where log-rates are piece-wise linear. In this article, we propose a Bayesian approach to calculating APC and AAPC values from age-adjusted cancer rate data.

Bayesian approach to cancer-trend analysis using age-stratified Poisson regression models

Author(s) Name: Pulak Ghosh, Kaushik Ghosh & Ram C Tiwari
Journal Name: Statistics in Medicine
Volume: Vol. 30, No. 2, PP 127-139, 30 January 2011
Year of Publication: 2011
Abstract:

Annual Percentage Change (APC) summarizes trends in age-adjusted cancer rates over short time-intervals. This measure implicitly assumes linearity of the log-rates over the intervals in question, which may not be valid, especially for relatively longer time-intervals. An alternative is the Average Annual Percentage Change (AAPC), which computes a weighted average of APC values over intervals where log-rates are piece-wise linear. In this article, we propose a Bayesian approach to calculating APC and AAPC values from age-adjusted cancer rate data.