Journal article
A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate
PloS one, Vol.14(5), p.e0216613
05/10/2019
DOI: 10.1371/journal.pone.0216613
PMCID: PMC6510436
PMID: 31075117
Abstract
Two decomposition methods have been widely used to attribute death differences between two populations to population size, age structure of the population, and age-specific mortality rate (ASMR), but their properties remain uninvestigated.
We assess how the two established decomposition methods yield varying results with three-factor factorial experimental designs, illustrating that they are sensitive to the choice of the reference group. We then propose a novel decomposition method to obtain robust decomposition results and use three cases to demonstrate its advantage.
The three decomposition methods differ fundamentally in their allocation of interactions to the contributions of the three factors. In comparison with the existing methods, the new method is robust to the choice of the reference group. Three case studies showed inconsistent attribution results for the two existing methods but robust results for the new method when the choice of the reference population changes.
The proposed method offers robust and more justifiable attribution results compared to the two existing methods. This method could be generalized to attribution of group differences of other health indicators.
Details
- Title: Subtitle
- A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate
- Creators
- Xunjie Cheng - Central South UniversityLiheng Tan - Central South UniversityYuyan Gao - Central South UniversityYang Yang - University of FloridaDavid C Schwebel - University of Alabama at BirminghamGuoqing Hu - Central South University
- Resource Type
- Journal article
- Publication Details
- PloS one, Vol.14(5), p.e0216613
- DOI
- 10.1371/journal.pone.0216613
- PMID
- 31075117
- PMCID
- PMC6510436
- NLM abbreviation
- PLoS One
- ISSN
- 1932-6203
- eISSN
- 1932-6203
- Grant note
- R37 AI032042 / NIAID NIH HHS
- Language
- English
- Date published
- 05/10/2019
- Academic Unit
- Research Administration
- Record Identifier
- 9984949179902771
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