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Implementing spatial segregation measures in R.

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This study introduces the R package "seg" for calculating residential segregation indices. It simplifies complex measurements, making social cohesion and integration analysis more accessible to researchers.

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Area of Science:

  • Sociology
  • Urban Studies
  • Demography

Background:

  • Estimating residential segregation is crucial for understanding societal integration.
  • Advanced segregation measures exist but are complex to calculate and underutilized.
  • Existing software solutions for segregation analysis have limitations.

Purpose of the Study:

  • To implement newly proposed segregation indices in an accessible R package.
  • To provide a flexible and user-friendly tool for calculating and analyzing residential segregation.
  • To overcome the computational complexity and accessibility barriers of advanced segregation measures.

Main Methods:

  • Developed the 'seg' package in R, an open-source statistical software environment.
  • Implemented several newly proposed segregation indices with detailed control over calculation parameters.
  • Included coercion methods for seamless integration with standard R statistical techniques.

Main Results:

  • The 'seg' package offers flexibility with user-friendly defaults for various skill levels.
  • Results can be directly used within R for further statistical analysis, eliminating the need for data export.
  • The package is free and open-source, enhancing accessibility for a broader research community.

Conclusions:

  • The 'seg' package democratizes the use of advanced residential segregation measures.
  • It facilitates more accurate and widespread analysis of social cohesion and integration.
  • This tool empowers researchers to conduct sophisticated segregation studies with greater ease.