Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations
(2015) In BMC Public Health 15.- Abstract
BACKGROUND: The methods currently available to estimate age- and sex-specific mortality rates for sub-populations are subject to a number of important limitations. We propose two alternative multivariable approaches: a relational model and a Poisson model both using restricted cubic splines.
METHODS: We evaluated a flexible Poisson and flexible relational model against the Elandt-Johnson approach in a simulation study using 100 random samples of population and death counts, with different sampling proportions and data arrangements. Estimated rates were compared to the original mortality rates using goodness-of-fit measures and life expectancy. We further investigated an approach for determining optimal knot locations in the... (More)
BACKGROUND: The methods currently available to estimate age- and sex-specific mortality rates for sub-populations are subject to a number of important limitations. We propose two alternative multivariable approaches: a relational model and a Poisson model both using restricted cubic splines.
METHODS: We evaluated a flexible Poisson and flexible relational model against the Elandt-Johnson approach in a simulation study using 100 random samples of population and death counts, with different sampling proportions and data arrangements. Estimated rates were compared to the original mortality rates using goodness-of-fit measures and life expectancy. We further investigated an approach for determining optimal knot locations in the Poisson model.
RESULTS: The flexible Poisson model outperformed the flexible relational and Elandt-Johnson methods with the smallest sample of data (1%). With the largest sample of data (20%), the flexible Poisson and flexible relational models performed comparably, though the flexible Poisson model displayed a slight advantage. Both approaches tended to underestimate infant mortality and thereby overestimate life expectancy at birth. The flexible Poisson model performed much better at young ages when knots were fixed a priori. For ages 30 and above, results were similar to the model with no fixed knots.
CONCLUSIONS: The flexible Poisson model is recommended because it derives robust and unbiased estimates for sub-populations without making strong assumptions about age-specific mortality profiles. Fixing knots a priori in the final model greatly improves fit at the young ages.
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- author
- Rachet, Bernard ; Maringe, Camille ; Woods, Laura M ; Ellis, Libby ; Spika, Devon LU and Allemani, Claudia
- publishing date
- 2015-12-16
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, England/epidemiology, Female, Humans, Infant, Infant, Newborn, Life Expectancy, Life Tables, Male, Middle Aged, Models, Statistical, Multivariate Analysis, Poisson Distribution, Young Adult
- in
- BMC Public Health
- volume
- 15
- pages
- 9 pages
- publisher
- BioMed Central (BMC)
- external identifiers
-
- scopus:84969766939
- pmid:27129577
- ISSN
- 1471-2458
- DOI
- 10.1186/s12889-015-2534-3
- language
- English
- LU publication?
- no
- id
- b00ebf13-7293-4867-8fbe-3c0ddcdd0be2
- date added to LUP
- 2019-06-10 13:42:39
- date last changed
- 2024-04-02 07:17:49
@article{b00ebf13-7293-4867-8fbe-3c0ddcdd0be2,
abstract = {{<p>BACKGROUND: The methods currently available to estimate age- and sex-specific mortality rates for sub-populations are subject to a number of important limitations. We propose two alternative multivariable approaches: a relational model and a Poisson model both using restricted cubic splines.</p><p>METHODS: We evaluated a flexible Poisson and flexible relational model against the Elandt-Johnson approach in a simulation study using 100 random samples of population and death counts, with different sampling proportions and data arrangements. Estimated rates were compared to the original mortality rates using goodness-of-fit measures and life expectancy. We further investigated an approach for determining optimal knot locations in the Poisson model.</p><p>RESULTS: The flexible Poisson model outperformed the flexible relational and Elandt-Johnson methods with the smallest sample of data (1%). With the largest sample of data (20%), the flexible Poisson and flexible relational models performed comparably, though the flexible Poisson model displayed a slight advantage. Both approaches tended to underestimate infant mortality and thereby overestimate life expectancy at birth. The flexible Poisson model performed much better at young ages when knots were fixed a priori. For ages 30 and above, results were similar to the model with no fixed knots.</p><p>CONCLUSIONS: The flexible Poisson model is recommended because it derives robust and unbiased estimates for sub-populations without making strong assumptions about age-specific mortality profiles. Fixing knots a priori in the final model greatly improves fit at the young ages.</p>}},
author = {{Rachet, Bernard and Maringe, Camille and Woods, Laura M and Ellis, Libby and Spika, Devon and Allemani, Claudia}},
issn = {{1471-2458}},
keywords = {{Adolescent; Adult; Aged; Aged, 80 and over; Child; Child, Preschool; England/epidemiology; Female; Humans; Infant; Infant, Newborn; Life Expectancy; Life Tables; Male; Middle Aged; Models, Statistical; Multivariate Analysis; Poisson Distribution; Young Adult}},
language = {{eng}},
month = {{12}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Public Health}},
title = {{Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations}},
url = {{http://dx.doi.org/10.1186/s12889-015-2534-3}},
doi = {{10.1186/s12889-015-2534-3}},
volume = {{15}},
year = {{2015}},
}