Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.
Mobile divides: gender, socioeconomic status, and mobile phone use in Rwanda
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
physics.soc-ph 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Coverage bias in GPS mobility data is source-specific and spatially dependent, with Facebook showing more even coverage than multi-app data and different dominant drivers for each.
citing papers explorer
-
Correcting socioeconomic bias in mobile phone mobility estimates using multilevel regression and poststratification
Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.
-
One country, multiple portraits: representativeness in GPS-based mobility data is source-specific and spatially dependent
Coverage bias in GPS mobility data is source-specific and spatially dependent, with Facebook showing more even coverage than multi-app data and different dominant drivers for each.