Table 3 Bias findings from validation studies in InfoUSA and Dun and Bradstreet business lists

Count accuracy

 Fleischhacker [8]

N/A

N/A

N/A

N/A

No differences found

No differences found

 Liese [15]

N/A

N/A

N/A

N/A

Urban areas had highest accuracy of stores. Rural areas had lowest accuracy of stores. Suburban areas had the lowest accuracy of restaurants

Urban areas had highest accuracy for stores and restaurants. Rural areas had lowest accuracy for stores and restaurants

 Liese [16]

Majority white neighborhoods had lowest accuracy

No differences found

High income and non-poor neighborhoods had lowest accuracy

No differences found

N/A

N/A

 Powell [17]

Majority black neighborhoods had lowest accuracy for food stores and restaurants. Majority non-Hispanic neighborhoods has lower accuracy for food stores

Majority black neighborhoods had lowest accuracy for restaurants and no difference for food stores

No differences found

High income areas had lowest accuracy for food stores and no differences for restaurants

Urban areas had highest accuracy of stores and restaurants. Rural areas had lowest accuracy of stores and restaurants

Urban areas had highest accuracy of stores and restaurants. Rural areas had lowest accuracy of stores and restaurants

Classification accuracy

 Han [23]

Majority non-Hispanic and majority black neighborhoods had lowest classification accuracy

Majority non-Hispanic and majority black neighborhoods had lowest classification accuracy

No differences found

No differences found

N/A

N/A

Locational accuracy

 Liese [15]

N/A

N/A

N/A

N/A

Urban areas were located with the least distance between observed and listed location. Records in suburban areas were most likely to be allocated to the correct census tract

Urban areas were located with the least distance between observed and listed location. Records in suburban areas were most likely to be allocated to the correct census tract