Using geographically weighted regression to explore spatial variation in survey data Article Swipe
Nonresponse can undermine the quality of social survey data. Understanding who does/does not respond to surveys is important for those involved in the collection and analysis of these data. Levels of nonresponse are known to vary geographically. However, there has been little consideration of how the predictors of survey nonresponse might vary geographically within countries. This study examines the possibility of spatial variation in response behavior using regional interactions and geographically weighted regression. Our results suggest that there is geographical variation in response behavior. Relying on “one size fits all” global models in nonresponse modelling might, therefore, be insufficient.
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Geography
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Statistics
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Demography
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Mathematics
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Philosophy
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Economics
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Physics
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Astrophysics
Concepts
Variation (astronomy)
Geographically Weighted Regression
Regression analysis
Survey data collection
Regression
Geography
Econometrics
Spatial variability
Data collection
Data quality
Non-response bias
Geographic variation
Quality (philosophy)
Statistics
Demography
Mathematics
Population
Sociology
Philosophy
Economics
Physics
Operations management
Epistemology
Astrophysics
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Metadata
- Type
- article
- Language
- en
- https://openaccess.city.ac.uk/id/eprint/14509/1/LahtinenBrunsdonButt_FINAL.pdf
- OA Status
- green
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2494706110
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