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Estimating the accuracy of geographical imputation.

Henry KA, Boscoe FP - Int J Health Geogr (2008)

Bottom Line: To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address.Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids.Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids.

View Article: PubMed Central - HTML - PubMed

Affiliation: New Jersey Department of Health & Senior Services, Cancer Epidemiology Services, New Jersey State Cancer Registry, Trenton, New Jersey, USA. kevin.henry@doh.state.nj.us

ABSTRACT

Background: To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address. Some analysts then use the postal code to assign information to the cases from finer-level geographies such as a census tract. Assignment is commonly completed using either a postal centroid or by a geographical imputation method which assigns a location by using both the demographic characteristics of the case and the population characteristics of the postal delivery area. To date no systematic evaluation of geographical imputation methods ("geo-imputation") has been completed. The objective of this study was to determine the accuracy of census tract assignment using geo-imputation.

Methods: Using a large dataset of breast, prostate and colorectal cancer cases reported to the New Jersey Cancer Registry, we determined how often cases were assigned to the correct census tract using alternate strategies of demographic based geo-imputation, and using assignments obtained from postal code centroids. Assignment accuracy was measured by comparing the tract assigned with the tract originally identified from the full street address.

Results: Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids. The addition of age characteristics increased the match rates even further. Match rates were highly dependent on both the geographic distribution of race/ethnicity groups and population density.

Conclusion: Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids. For a specific analysis, researchers will still need to consider the potential impact of geocoding quality on their results and evaluate the possibility that it might introduce geographical bias.

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Procedures used for geo-imputation.
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Figure 2: Procedures used for geo-imputation.

Mentions: The geo-imputation method used for this study assigns a census tract to a case based on the fraction of the population from each tract located within the bounds of each postal ZIP code. Tracts having a greater fraction of the population have a higher probability of being assigned to cases. Our imputation procedure required three steps (Figure 2). First, using the tract population fractions for each population subgroup in each postal ZIP code, we calculated cumulative probabilities. Second, we assigned a random number between 0–1 to each case using the SAS function 'ranuni'. Finally, we interleaved the random numbers into the census tract cumulative probabilities for each ZIP code and assigned each case a census tract based on where the random number fell within the range of cumulative probabilities. Figure 2 provides a hypothetical example for imputing cases with ZIP codes 07001 and 07935. All geo-imputation steps were completed in SAS v. 9.1 [37].


Estimating the accuracy of geographical imputation.

Henry KA, Boscoe FP - Int J Health Geogr (2008)

Procedures used for geo-imputation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2266732&req=5

Figure 2: Procedures used for geo-imputation.
Mentions: The geo-imputation method used for this study assigns a census tract to a case based on the fraction of the population from each tract located within the bounds of each postal ZIP code. Tracts having a greater fraction of the population have a higher probability of being assigned to cases. Our imputation procedure required three steps (Figure 2). First, using the tract population fractions for each population subgroup in each postal ZIP code, we calculated cumulative probabilities. Second, we assigned a random number between 0–1 to each case using the SAS function 'ranuni'. Finally, we interleaved the random numbers into the census tract cumulative probabilities for each ZIP code and assigned each case a census tract based on where the random number fell within the range of cumulative probabilities. Figure 2 provides a hypothetical example for imputing cases with ZIP codes 07001 and 07935. All geo-imputation steps were completed in SAS v. 9.1 [37].

Bottom Line: To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address.Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids.Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids.

View Article: PubMed Central - HTML - PubMed

Affiliation: New Jersey Department of Health & Senior Services, Cancer Epidemiology Services, New Jersey State Cancer Registry, Trenton, New Jersey, USA. kevin.henry@doh.state.nj.us

ABSTRACT

Background: To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address. Some analysts then use the postal code to assign information to the cases from finer-level geographies such as a census tract. Assignment is commonly completed using either a postal centroid or by a geographical imputation method which assigns a location by using both the demographic characteristics of the case and the population characteristics of the postal delivery area. To date no systematic evaluation of geographical imputation methods ("geo-imputation") has been completed. The objective of this study was to determine the accuracy of census tract assignment using geo-imputation.

Methods: Using a large dataset of breast, prostate and colorectal cancer cases reported to the New Jersey Cancer Registry, we determined how often cases were assigned to the correct census tract using alternate strategies of demographic based geo-imputation, and using assignments obtained from postal code centroids. Assignment accuracy was measured by comparing the tract assigned with the tract originally identified from the full street address.

Results: Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids. The addition of age characteristics increased the match rates even further. Match rates were highly dependent on both the geographic distribution of race/ethnicity groups and population density.

Conclusion: Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids. For a specific analysis, researchers will still need to consider the potential impact of geocoding quality on their results and evaluate the possibility that it might introduce geographical bias.

Show MeSH
Related in: MedlinePlus