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Applied Spatial Analysis and Policy

, Volume 4, Issue 4, pp 281–300 | Cite as

Internal and External Validation of Spatial Microsimulation Models: Small Area Estimates of Adult Obesity

  • Kimberley L. Edwards
  • Graham P. Clarke
  • James Thomas
  • David Forman
Article

Abstract

Spatial microsimulation models can be used to estimate previously unknown data at the micro-level, although validation of these models can be challenging. This paper seeks to describe an approach to validation of these models. Obesity data in adults were estimated at the small area level using a static, deterministic, spatial microsimulation model called SimObesity. This model utilised both Census 2001 data and the Health Survey for England for 2004–2006. Regression analysis was used to identify the covariates that were the strongest predictors of obesity and these were used as the model input variables. The model was calibrated using regression and equal variance t-tests. Two methods of external validation were undertaken; aggregating obesity data to a coarser geographical level at which obesity data was available, and secondly using small area level cancer data for tumour sites known to be correlated to obesity. The output obesity data were mapped and statistically significant hot (cold) spots of high (low) prevalence of obesity identified. Both internal and external validation showed low errors, suggesting this was a satisfactory simulation. Statistically significant hot and cold spots of (simulated) obesity prevalence existed, even after adjusting for age. This paper emphasises three steps to validation of spatial microsimulation models: 1. Accurate simulations require strong correlations between the input and output variables; 2. It is essential to internally validate the models; 3. Use all means possible to externally validate the model.

Keywords

Obesity Small area estimation Spatial microsimulation modelling 

Notes

Acknowledgements

KLE would like to thank NATSEM, University of Canberra, for the invite to spend a sabbatical with them working on spatial microsimulation modelling techniques. The 2001 Census statistics and boundary data used in this paper are Crown Copyright produced by the Office for National Statistics. Licensed for academic use by the Economic and Social Research Council and the Joint Information Systems Committee Census Programme. The Census data service provider is the Census Dissemination Unit through the Manchester Information and Associated Services (MIMAS) of Manchester Computing, University of Manchester, through an interface called CASWEB. The boundary data service provider is the Census Geography Data Unit (UK Boundary Outline and Reference Database for Education and Research Study: UKBORDERS) via Edinburgh University Data Library. The 2001 Census Super Output Area and Ward Boundaries are Crown copyright 2003 where Crown copyright material is reproduced with the permission of the Controller of HMS. The national surveys are available from UK Data Archives managed by the University of Essex (http://www.data-archive.ac.uk/).

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Kimberley L. Edwards
    • 1
  • Graham P. Clarke
    • 2
  • James Thomas
    • 1
  • David Forman
    • 1
  1. 1.Centre of Epidemiology and BiostatisticsUniversity of LeedsLeedsUK
  2. 2.School of GeographyUniversity of LeedsLeedsUK

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