The links are for required readings found in the Walden databases ONLY. For all other readings, see your course resources.
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Al-Owais, A., Al-Suwaidi, K., Amiri, N., Carter, A. O., Hossain, M. M., & Sheek-Hussein, M. M. (2000). Use of existing data for public health planning: A study of the prevalence of hepatitis B surface antigen and core antibody in Al Ain Medical District, United Arab Emirates. World Health Organization. Bulletin of the World Health Organization, 78(11), 1324–1329.
Aponte, J. (2010). Key elements of large survey data sets. Nursing Economics, 28(1), 27–36.
Atkinson, M. D., Brophy, S., Siebert, S., Gravenor, M. B., Phillips, C., Ford, D. V., . . . Lyons, R. A. (2010). Protocol for a population-based ankylosing spondylitis (PAS) cohort in Wales. BMC Musculoskeletal Disorders, 11(1), 197.
Cox, E., Martin, B. C., Van Staa, T., Garbe, E., Siebert, U., & Johnson, M. L. (2009). Good research practices for comparative effectiveness research: Approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: The International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report—Part II. Value in Health, 12(8), 1053–1061.
Curtin, C., Anderson, S. E., Must, A., & Bandini, L. (2010). The prevalence of obesity in children with autism: A secondary data analysis using nationally representative data from the national survey of children’s health. BMC Pediatrics, 10(1), 11.
Doolan, D. M., & Froelicher, E. S. (2009). Using an existing data set to answer new research questions: A methodological review. Research and Theory for Nursing Practice, 23(3), 203–215.
Evans, E., Grella, C. E., Murphy, D. A., & Hser, Y. (2010). Using administrative data for longitudinal substance abuse research. The Journal of Behavioral Health Services & Research, 37(2), 252–271.
French, D. D., Campbell, R. R., Rubenstein, L. Z., & Spehar, A. M. (2008). Acquisition costs and use of Medicare Part D-excluded drugs in Veterans Health Administration long-stay nursing home residents: A national, descriptive, secondary data analysis. Drugs & Aging, 25(10), 855–860.
Fuller, C. H. (1974). Weighting to adjust for survey nonresponse. Public Opinion Quarterly, 38(2), 239–246.
Fullerton, S. M., & Lee, S. S. (2011). Secondary uses and the governance of de-identified data: Lessons from the human genome diversity panel. BMC Medical Ethics, 12(1), 16.
Gomez, M. R. (1997). Recommendations for optimizing the usefulness of existing exposure databases for public health applications. AIHA Journal, 58(3), 181–182.
Hansen, C. (2012, March 14). Unlocking our data to save lives: Analyzing existing electronic health care records could help B.C. residents and save the province billions in costs. The Vancouver Sun, p. A11.
Hofferth, S. L. (2005). Secondary data analysis in family research. Journal of Marriage and Family, 67(4), 891–907.
Iversen, A., Waterdrinker, A., Fear, N., Greenberg, N., Barker, C., Hotopf, M., . . . Wessely, S. (2007). Factors associated with heavy alcohol consumption in the U.K. Armed Forces: Data from a health survey of Gulf, Bosnia, and Era Veterans. Military Medicine, 172(9), 956–961.
Kamin, L. F. (2010). Using a five-step procedure for inferential statistical analyses. The American Biology Teacher, 72(3), 186–188.
Kelder, J-A. (2005). Using someone else’s data: Problems, pragmatics and provisions. Forum: Qualitative Social Research, 6(1), 1–13.
Langkamp, D. L., Lehman, A., & Lemeshow, S. (2010). Techniques for handling missing data in secondary analyses of large surveys. Academic Pediatrics, 10(3), 205–210.
Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. (2009). Can differences in medical drug compliance between European countries be explained by social factors: Analyses based on data from the European Social Survey, round 2. BMC Public Health, 9, 145–150.
Lipowski, E. E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17), 1667–1670.
Long, J. A., Bamba, M. I., Ling, B., & Shea, J. A. (2006). Missing race/ethnicity data in Veterans Health Administration based disparities research: A systematic review. Journal of Health Care for the Poor and Underserved, 17(1), 128–140.
Maiti, T. (2005). Tutorials in biostatistics, vol. 1: Statistical methods in clinical studies / tutorials in biostatistics, vol. 2: Statistical modelling of complex medical data. Journal of the American Statistical Association, 100(472), 1468–1468. (Open PDF and scroll to p. 1468 to access this book review.)
Marshall, G., & Jonker, L. (2010a). A concise guide to… descriptive statistics. Synergy, 22–25.
Marshall, G., & Jonker, L. (2010b). A concise guide to inferential statistics. Synergy, 20–24.
McHugh, M. L. (2003a). Descriptive statistics, part I: Level of measurement. Journal for Specialists in Pediatric Nursing, 8(1), 35–37.
McHugh, M. L. (2003b). Descriptive statistics, part II: Most commonly used descriptive statistics. Journal for Specialists in Pediatric Nursing, 8(3), 111–116.
McPhail, D., Goodwin, I., Gordon, K. (2006). Reviewing statistical analysis plans—A guide for medical writers. Drug Information Journal, 40(2), 197–202.
Negin, J., & Cumming, R. G. (2010). HIV infection in older adults in Sub-Saharan Africa: Extrapolating prevalence from existing data. World Health Organization. Bulletin of the World Health Organization, 88(11), 847–853.
Pearce, A., Jenkins, R., Kirk, C., & Law, C. (2008). An evaluation of UK secondary data sources for the study of childhood obesity, physical activity and diet. Child: Care, Health and Development, 34(6), 701–709.
Pierannunzi, C., Town, M., Garvin, W., Shaw, F. E., & Balluz, L. (2012). Methodologic changes in the behavioral risk factor surveillance system in 2011 and potential effects on prevalence estimates. MMWR: Morbidity & Mortality Weekly Report, 61(22), 410–413.
Pike, G. R. (2008). Using weighting adjustments to compensate for survey nonresponse. Research in Higher Education, 49(2), 153–171.
Preisser, J. S., & Koch, G. G. (1997). Categorical data analysis in public health. Annual Review of Public Health, 18, 51–82.
Putting existing data to work to improve quality care. (2004). Quality Letter for Healthcare Leaders, 16(3), 2–9, 1.
Silva-Ayçaguer, L. C., Suárez-Gil, P., & Fernández-Somoano, A. (2010). The null hypothesis significance test in health sciences research (1995–2006): Statistical analysis and interpretation. BMC Medical Research Methodology, 10(1), 44.
Smith, A. K., Ayanian, J. Z., Covinsky, K. E., Landon, B. E., McCarthy, E. P., Wee C. C., & Steinman, M. A. (2011). Conducting high-value secondary dataset analysis: An introductory guide and resources. Journal of General Internal Medicine, 26(8), 920–929.
Smith, P. M., Stock, S. R., McLeod, C. B., Koehoorn, M., Marchand, A., & Mustard, C. A. (2010). Research opportunities using administrative databases and existing surveys for new knowledge in occupational health and safety in Canada, Quebec, Ontario and British Columbia. Canadian Journal of Public Health, 101, S46–S52.
Thebane, L., & Akhtar-Danesh, N. (2008). Guidelines for reporting descriptive statistics in health research. Nurse Researcher, 15(2), 72–81.
Von Elm E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Bulletin of the World Health Organization, 85(11), 867–872.
Wang, R., Sedransk, J., & Jinn, J. H. (1992). Secondary data analysis when there are missing observations. Journal of the American Statistical Association, 87(420), 952–961.
Whitener, B. L., Van Horne, V. V., & Gauthier, A. K. (2005). Health services research tools for public health professionals. American Journal of Public Health, 95(2), 204–207.
Wirehn, A., Karlsson, H., & Carstensen, J. (2007). Estimating disease prevalence using a population-based administrative healthcare database. Scandinavian Journal of Public Health, 35(4), 424–431.
Wolverton, M. L. (2009). Research design, hypothesis testing, and sampling. The Appraisal Journal, 77(4), 370–382.
Yiannakoulias, N. (2011). Understanding identifiability in secondary health data. Canadian Journal of Public Health, 102(4), 291–293.
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