OBJECTIVE: To test the accuracy of imputing a practice population's average socioeconomic characteristics (such as average education levels and average income) using census data centred on the location of the practice. DESIGN: Comparison of census data with survey data collected in primary care offices. SETTING: Ontario. PARTICIPANTS: A cross-sectional sample of patients from 116 urban practices. MAIN OUTCOME MEASURES: Patient data were compared with census data at different levels of aggregation using mean absolute relative error (ARE), median ARE, and Spearman rank correlations. RESULTS: A total of 4413 patient surveys were collected. Differences between patient profiles and census data were large. Most mean AREs were clustered between 0.70 and 0.80, and median AREs were as high as 1.67. Correlations were low (ρ = 0.02) to moderate (ρ = 0.48). These results held across both levels of aggregation. CONCLUSION: The use of imputation techniques based on practice location is inadvisable, given the large differences that were observed.
OBJECTIVE: To test the accuracy of imputing a practice population's average socioeconomic characteristics (such as average education levels and average income) using census data centred on the location of the practice. DESIGN: Comparison of census data with survey data collected in primary care offices. SETTING: Ontario. PARTICIPANTS: A cross-sectional sample of patients from 116 urban practices. MAIN OUTCOME MEASURES: Patient data were compared with census data at different levels of aggregation using mean absolute relative error (ARE), median ARE, and Spearman rank correlations. RESULTS: A total of 4413 patient surveys were collected. Differences between patient profiles and census data were large. Most mean AREs were clustered between 0.70 and 0.80, and median AREs were as high as 1.67. Correlations were low (ρ = 0.02) to moderate (ρ = 0.48). These results held across both levels of aggregation. CONCLUSION: The use of imputation techniques based on practice location is inadvisable, given the large differences that were observed.
Authors: Simone Dahrouge; William Hogg; Grant Russell; Robert Geneau; Elizabeth Kristjansson; Laura Muldoon; Sharon Johnston Journal: Open Med Date: 2009-09-01
Authors: Elizabeth A Mertz; Cynthia D Wides; Aubri M Kottek; Jean Marie Calvo; Paul E Gates Journal: Health Aff (Millwood) Date: 2016-12-01 Impact factor: 6.301
Authors: Simone Dahrouge; William Hogg; Natalie Ward; Meltem Tuna; Rose Anne Devlin; Elizabeth Kristjansson; Peter Tugwell; Kevin Pottie Journal: BMC Health Serv Res Date: 2013-12-17 Impact factor: 2.655