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March 3, 2026
Heteroskedastic Choice-Based Sampling Spatial Choice Models: Application to cancer modeling
SD
Sophie Dabo-Niang
Université de Lille
Puntos clave
A significant advancement was achieved by applying spatial choice models to cancer modeling, facilitating better data interpretation.
Key metrics showed bias correction effectiveness in heteroskedastic sampling scenarios, leading to enhanced prediction accuracy.
Methodological innovations centered around heteroskedastic choice-based sampling, effectively optimizing model accuracy in diverse datasets.
Implications suggest that improved modeling of cancer trends can assist in public health planning and resource allocation.
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International audience
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Sophie Dabo-Niang (Tue,) studied this question.
synapsesocial.com/papers/69a75ba4c6e9836116a235ad
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Heteroskedastic Choice-Based Sampling Spatial Choice Models: Application to cancer modeling | Synapse