Assessing Spatial Equity in Pre-K Interventions: A Tutorial on Geographically Weighted Regression

• In Event: Research Methodologies in Education

Abstract

Effective implementation of pre-k interventions requires efficient distribution of the limited resources to the target population. Thus, assessing equity levels in resource distribution is an important obligation of early childhood education agencies. The use of ordinary least squares (OLS) regression for conducting such assessments ignores important spatial variations inherent in georeferenced data. We provide a tutorial illustrating the geographically weighted regression (GWR) as a tool for assessing spatial equity in pre-k resource distribution, using data for the Great Start Readiness Program locations in Michigan. The GWR outperformed the OLS and produced additional insights into the spatial pattern of the relationships among the model variables. This illustration broadens methodology and research scope for investigators dealing with equity in education resource distribution

Authors

• Hope O. Akaeze, Michigan State University
  Presenting Author

• Jamie Wu, Michigan State University
  Non-Presenting Author