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1. Roos LL, Nicol JP, Cageorge SM. Using administrative data for longitudinal research: comparisons with primary data collection. Journal of Chronic Diseases 1987; 40: 41-9.

2. Lezzoni LI. Using administrative data to study persons with disabilities.The Milbank Quarterly 2002; 80(2): 347-79.

3. Brackstone G.J. Issues in the use of administrative records for statistical purposes. Survey Methodology 1987; 13: 29-43.

4. Disano J, Goulet J, Muhajarine N, et al. Social-economic status and rates of hospital admission for chronic disease in urban Canada. The Canadian Nurse 2010; 106(1): 24-9.

5. Booth GL, Bisara P, Lipscombe LL, et al.  Universal drug coverage and socioeconomic disparaties in major diabetes outcomes. Diabetes Care 2012; epub ahead of print.

6. Wilkins R, Berthelot JM, Ng E. Trends in mortality by neighbourhood income in urban Canada from 1971 to 1996. Health Reports 2002; 13: 1-28.

7. Hanley GE, Morgan S. On the validity of area-based income measures to proxy household income. BMC Health Services Research 2008; 8: 79.

8. Marra CA, Lynd LD, Harvard SS, Grubisic X. Agreement between aggregate and individual-level measures of income and education: a comparison across three patient groups. BMC Health Services Research 2011; 11: 69.

9. Southern DA, McLaren L, Hawe P, et al. Individual-level and neighbourhood income measures: agreement and association with outcomes in a cardiac disease cohort. Medical Care 2005; 43(11): 1116-22.

10. Pampalon R, Hamel D, Gamache P. A comparison of individual and area-based socio-economic data for monitoring social inequalities in health. Health Reports 2009; 20(4): 85-94.

11. Burnett RT, Cakmak S, Brion O, et al. An indirect adjustment method for multiple missing variables applicable to environmental epidemiology. American Journal of Epidemiology. Under review.

12. Rotermann M. Evaluation of the coverage of linked Canadian Community Health Survey and hospital inpatient records. Health Reports (Statistics Canada, Catalogue 82-003) 2009; 20(1): 45-51.

13. Wilkins K, Shields M, Rotermann M. Smokers’ use of acute care hospitals: A prospective study. Health Reports 2009; 20(4): 75-83.

14. Sanmartin C, Khan S. Hospitalizations for Ambulatory Care Sensitive Conditions (ACSC): The Factors That Matter. Health Research Working Paper Series (Catalogue 82-622-X, No. 007) Ottawa: Statistics Canada, 2011.

15. Wilkins R, Tjepkema M, Mustard C, Choinière R. The Canadian census mortality follow-up study, 1991 through 2001. Health Reports 2008; 19(3): 25-43.

16. Peters PA, Tjepkema M. 1991-2011 Canadian census mortality and cancer follow-up study. Proceedings of Statistics Canada Symposium 2010. Social Statistics: The Interplay among Censuses, Surveys and Administrative Data (Catalogue. 11-522-XCB) Ottawa: Statistics Canada, 2011:150-6.

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18. Statistics Canada, Household Survey Methods Division. External Linkage of Person-oriented Information 1992/93 to 2000/01 HospitalMorbidity Files. (unpublished). Ottawa: Statistics Canada, 2003.

19. Nadeau C. Linking HPOI 1992-2005 to CCHS. Household Suvey Methods Division internal documents. Ottawa: Statistics Canada, 2007.

20. Wong S, Shields M, Leatherdale S, et al. Assessment of validity of self-reported smoking status. Health Reports 2012; 23(1): 47-53.

21. Hanley JA, McNeil BJ. The meaning and use of the area under a Receiver Operating Characteristic (ROC) Curve.  Diagnostic Radiology 1982; 143(1): 29-36.

22.Metz CE. Basic principles of ROC analysis. Seminars in Nuclear Medicine 1978; 8(4): 283-98.

23. Streiner DL, Cairney JC. What’s under the ROC? An introduction to Receiver-Operating Characteristics Curves. The Canadian Journal of Psychiatry 2007; 52(2): 121-8.

24. Swets JA, Dawes RM, Monahan J. Psychological science can improve diagnostic decision. Psychological Science in the Public Interest 2000; 1(1): 1-26.

25. Balinuas D, Patra J, Rehm J, et al. Smoking-attributable morbidity: acute care hospital diagnoses and days of treatment in Canada, 2002. BMC Public Health 2007; 7: 247.

26. Rosella LC, Manuel DG, Burchill C, Stukel TA. A population-based risk algorithm for the development of diabetes: development and validation of the Diabetes Population Risk Tool (DPort). Journal of Epidemiology and Community Health 2011; 65(7): 613-20.

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