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S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem

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  • Juan C Duque
  • Henry Laniado
  • Adriano Polo

Abstract

This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP.

Suggested Citation

  • Juan C Duque & Henry Laniado & Adriano Polo, 2018. "S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-25, November.
  • Handle: RePEc:plo:pone00:0207377
    DOI: 10.1371/journal.pone.0207377
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    References listed on IDEAS

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    2. Gareth Simons, 2023. "The cityseer Python package for pedestrian-scale network-based urban analysis," Environment and Planning B, , vol. 50(5), pages 1328-1344, June.

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