When data are not missing at random: Implications for measuring health conditions in the Behavioral Risk Factor Surveillance System

BMJ Open

Volumn 2, Issue 4, 2012, Pages

  Frankel, Martin R ^a   Battaglia, Michael P ^b   Balluz, Lina ^c   Strine, Tara ^c  

^a CITY UNIVERSITY OF NEW YORK   (United States)

^b ABT ASSOCIATES   (United States)

^c CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BEHAVIORAL RISK FACTOR SURVEILLANCE SYSTEM; CROSS-SECTIONAL STUDY; DEMOGRAPHY; DEPRESSION; HEALTH; HEALTH SURVEY; HOSPITAL MANAGEMENT; HOUSEHOLD; HUMAN; HUMAN EXPERIMENT; MEDICAL RECORD; NORMAL HUMAN; PUBLIC HEALTH SERVICE; TELEPHONE;

EID: 84864265407     PISSN: None     EISSN: 20446055     Source Type: Journal    
DOI: 10.1136/bmjopen-2011-000696     Document Type: Article

References (21)

1. Botman SL, Moore TF, Moriarity CL, et al. Design and estimation for the National Health Interview Survey, 1995-2004. Vital Health Stat 2 2000;130:1-31.
2. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey Data. http://www.cdc.gov/nchs/tutorials/nhanes/SurveyDesign/ Weighting/intro.htm (accessed 9 Nov 2011).
3. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Operational and User's Guide, Version 3.0. Atlanta, GA: Centers for Disease Control and Prevention, 2006. ftp://ftp.cdc.gov/pub/Data/ Brfss/userguide.pdf (accessed 9 Nov 2011).
4. Korn EL, Graubard BI. Analysis of Health Surveys. New York: John Wiley & Sons, 1999.
5. Kalton G. Compensating for Missing Survey Data. Ann Arbor, MI: Institute for Social Research, 1983.
6. Lin TH. Missing data imputation in quality-of-life assessment: imputation for WHOQOL-BREF. Pharmacoeconomics 2006;14:917-25.
7. Shrive FM, Stuart H, Quan H, et al. Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Med Res Methodol 2006;6:57.
8. Durrant GB. Imputation methods for handling item-nonresponse in practice: methodological issues and recent debates. Int J Soc Res Methodol 2009;12:293-304.
9. Cantwell PJ, Hogan H, Styles KM. Imputation, apportionment and statistical methods in the U.S. Census: issues surrounding Utah v. Evans. U.S. Census Bureau Research Report Series, Statistics 2005-01. Washington, DC: U.S. Census Bureau, Statistical Research Division, 2005. http://www.census.gov/srd/ www/byyear.html (accessed 2 May 2012).
10. Schenker N, Raghunathan TE, Chiu P, et al. Multiple Imputation of Family Income and Personal Earnings in the National Health Interview Survey: Methods And Examples. 2010. http://www.cdc.gov/nchs/data/nhis/tecdoc4.pdf (accessed 2 May 2012).
11. Centers for Disease Control and Prevention. 2006 Behavioral Risk Factor Surveillance System Summary Data Quality Report. Atlanta, GA: US Department of Health and Human Services, CDC, 2007. ftp://ftp.cdc.gov/pub/Data/Brfss/ 2006SummaryDataQualityReport.pdf (accessed 2 May 2012).
12. Rubin DB. Inference and missing data. Biometrika 1976;29:581-92.
13. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System: At a Glance 2010. Atlanta, GA: US Department of Health and Human Services, CDC, 2010. http://www.cdc.gov/chronicdisease/resources/ publications/AAG/brfss.htm (accessed 2 May 2012).
14. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study and the Patient Health Questionnaire Primary Care Study Group. JAMA 1999;282:1737-44. (Pubitemid 29533604)
15. Shafer J. Analysis of Incomplete Multivariate Data. London: Chapman and Hall, 1997.
16. Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd edn. New York: John Wiley & Sons, 2000.
17. Izrael D, Battaglia AA, Hoaglin DC, et al. SAS macros and tools for working with weighted logistic regression models that use survey data. SAS Users Group International 28 Proceedings. Cary, NC: SAS Institute Inc, 2003:2paper 75-28.
18. Rubin DB. Multiple Imputation for Nonresponse in Surveys . New York: John Wiley & Sons, 1987.
19. Kish L. Survey Sampling . New York: John Wiley & Sons, 1965. section 12.4.
20. Berglund PA. An introduction to multiple imputation of complex sample data using SAS v9.2. SAS Global Forum Proceedings. Cary, NC: SAS Institute Inc. 2010: paper 265-2010.
21. Shlomo N. Statistical disclosure control methods for census frequency tables. Int Stat Rev 2007;75:199-217.