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Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations

Rachet, Bernard; Maringe, Camille; Woods, Laura M; Ellis, Libby; Spika, Devon LU and Allemani, Claudia (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
publishing date
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
external identifiers
  • scopus:84969766939
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
2019-07-24 11:06:14
@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},
  keyword      = {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},
  pages        = {9},
  publisher    = {BioMed Central},
  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},
  volume       = {15},
  year         = {2015},
}