Purpose of Addressing Selection Bias
This page explains selection bias as it applies to Cairo residential listings data. The objective is to clarify how the mechanisms that determine which properties are listed introduce systematic distortions in visibility, independent of residential reality.
Selection bias is treated as an inherent feature of platform-mediated exposure rather than an analytical error.
Listings as a Self-Selected Sample
Residential listings represent properties that are voluntarily published through specific platforms. This publication depends on owner choice, intermediary practices, platform access, and perceived relevance of listing exposure.
As a result, the dataset reflects a self-selected subset of residential properties rather than a comprehensive or random sample.
Drivers of Selection Bias
Selection bias arises from multiple structural factors, including differential platform adoption across districts, varying reliance on intermediaries, and selective publication of certain property types or arrangements.
These drivers shape what becomes visible without reference to overall housing presence or distribution.
Consequences for Interpretation
Because selection is not random, patterns observed in listings cannot be extrapolated to the broader residential environment. Apparent concentrations, absences, or category prominence reflect publication behavior rather than housing structure.
Any interpretation that assumes representativeness exceeds the dataset’s epistemic scope.
Selection Bias as a Decision Boundary
Selection bias defines a clear decision boundary for dataset use. Listings can explain how properties are exposed but cannot support conclusions about what is typical, prevalent, or dominant within Cairo’s residential landscape.
This page establishes selection bias as a foundational constraint on all listing-based interpretation.