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


Rachet, B; Maringe, C; Woods, LM; Ellis, L; Spika, D; Allemani, C; (2015) Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations. BMC Public Health, 15. p. 1240. ISSN 1471-2458 DOI: 10.1186/s12889-015-2534-3

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Abstract

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. 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. 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. 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.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology
Research Centre: Cancer Survival Group
PubMed ID: 27129577
URI: http://researchonline.lshtm.ac.uk/id/eprint/2550752

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