Quantifying bias in a health survey: Modeling total survey error in the National Immunization Survey

Statistics in Medicine

Volumn 30, Issue 5, 2011, Pages 505-514

  Molinari, NoelleAngelique M ^a   Wolter, Kirk M ^b   Skalland, Benjamin ^b   Montgomery, Robert ^b   Khare, Meena ^c   Smith, Philip J ^a   Barron, Martin L ^b   Copeland, Kennon ^b   Santos, Kathleen ^b   Singleton, James A ^a  

^a NATIONAL CENTER FOR IMMUNIZATION AND RESPIRATORY DISEASES   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

^c NATIONAL CENTER FOR HEALTH STATISTICS   (United States)

Author keywords

Monte Carlo simulation; Noncoverage bias; Nonresponse bias; Survey methodology; Total survey error

Indexed keywords

ARTICLE; CLINICAL EVALUATION; CONTROLLED STUDY; HEALTH SURVEY; MASS IMMUNIZATION; MATHEMATICAL MODEL; MONTE CARLO METHOD; NATIONAL HEALTH SERVICE; NONRESPONSE BIAS; NORMAL DISTRIBUTION; PREVENTIVE HEALTH SERVICE; PROCESS DEVELOPMENT; QUANTITATIVE ANALYSIS; SENSITIVITY ANALYSIS; TELECONSULTATION; TREATMENT RESPONSE;

ALGORITHMS; BIAS (EPIDEMIOLOGY); CELLULAR PHONE; CHILD, PRESCHOOL; COMPUTER SIMULATION; DATA COLLECTION; HEALTH PERSONNEL; HEALTH SURVEYS; HUMANS; IMMUNIZATION PROGRAMS; INFANT; INTERVIEWS AS TOPIC; MODELS, STATISTICAL; MONTE CARLO METHOD; NORMAL DISTRIBUTION; PARENTAL CONSENT; UNITED STATES; VACCINATION;

EID: 79851470205     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3911     Document Type: Article

References (24)

1. Mulry MH, Spencer BD. Total error in PES estimates of population. Journal of the American Statistical Association 1991; 86:839-863.
2. Blumberg SJ, Luke JV, Cynamon ML. Telephone coverage and health survey estimates: evaluating the need for concern about wireless substitution. American Journal of Public Health 2006; 96:926-931.
3. Battaglia MP, Khare M, Frankel MR, Murray MC, Buckley P, Peritz S. Response rates: how have they changed and where are they headed? In Advances in Telephone Survey Methodology, Lepkowski JM, Tucker C, Brick JM, Leeuw ED, Japec L, Lavrakas PJ, Link MW, Sangster RL(eds), Chapter 24. Wiley: New York, 2007.
4. de Leeuw E, de Heer W. Trends in household survey nonresponse: a longitudinal and international comparison. In Survey Nonresponse, Groves RM, Dillman DA, Eltinge JL, Little R(eds). Wiley: New York, 2002.
5. Link MW, Mokdad AH, Kulp D, Hyon A. Has the national do not call registry helped or hurt state-level response rates? A time series analysis. Public Opinion Quarterly 2006; 70:794-809.
6. Smith PJ, Hoaglin DC, Battaglia MP, Khare M, Barker LE. Statistical Methodology of the National Immunization Survey: 1994-2002. Vital and Health Statistics, Series 2: Data Evaluation and Methods Research, vol. 138. National Center for Health Statistics: Hyattsville, MD, 2005.
7. Groves RM. Nonresponse rates sand nonresponse bias in household surveys. Public Opinion Quarterly 2006; 70:646-675.
8. Groves RM, Couper MP. Nonresponse in Household Interview Surveys. Wiley: New York, 1998.
9. Skalland B, Wolter K, Shin HC, Blumberg SJ. A non-response bias analysis to inform use of incentives in multistage RDD telephone surveys. The 2006 Joint Statistical Meetings, Seattle, WA, 2006.
10. Johnson TP, Cho YI, Campbell RT, Holbrook AL. Using community-level correlates to evaluate nonresponse effects in a telephone survey. Public Opinion Quarterly 2006; 70:704-719.
11. Smith PJ, Marsh LC. Evaluating assumptions of weighting class methods for partial nonresponse using a selection model. Statistics in Medicine 2008; 27:4569-4580.
12. Lash TL, Fink AK. Semi-automated sensitivity analysis to assess systematic errors in observational data. Epidemiology 2003; 14:451-458.
13. Phillips CV. Quantifying and reporting uncertainty from systematic errors. Epidemiology 2003; 14:459-466.
14. Greenland S. Multiple-bias modeling for analysis of observational data. Journal of the Royal Statistical Society A 2005; 168:267-306.
15. Lash TL. Heuristic thinking sand inference from observational epidemiology. Epidemiology 2007; 18:67-72.
16. Hogan H, Wolter KM. Measuring accuracy in a post-enumeration survey. Survey Methodology 1988; 14:99-116.
17. Centers for Disease Control and Prevention. Recommended Childhood and Adolescent Immunization Schedule-United States. MMWR 2006; 54(52):Q1-Q4.
18. Brick JM, Waksberg J, Kulp D, Starer A. Bias in list-assisted telephone samples. Public Opinion Quarterly 1995; 59(2):218-235.
19. Dutwin D, Kulp D, Herrmann M, Rapoport R, Fahimi M. A comparison of landline telephone households in zero-banks to those in a traditional RDD sample: is lack of coverage a source of bias? American Association of Public Opinion Research Annual Meetings, Hollywood, FL, May 2009.
20. Fahimi M, Kulp D. Bias in list-assisted 100-series RDD Sampling. Survey Practice, June 2009 Issue. Available from: [19 August 2009].
21. Khare M, Chowdhury S. An evaluation of methods to compensate for noncoverage of nontelephone households using information on interruptions in telephone service and presence of wireless phones. Proceeding of the Joint Statistical Meetings Section on Survey Research Methods. American Statistical Association: Alexandria, VA, 2006; 3221-3228 [CD-ROM].
22. Khare M, Chowdhury S, Wolter K, Singleton J. An assessment of bias due to noncoverage of wireless only households in RDD surveys. Proceeding of the Joint Statistical Meetings Section on Survey Research Methods. American Statistical Association: Alexandria, VA, 2007; 3911-3918 [CD-ROM].
23. American Association for Public Opinion Research. Standard Definitions. Ann Arbor, MI. American Association for Public Opinion Research, 2008. Available From:. Last accessed 25 September 2008.
24. Link MW, Daily G, Shuttles CD, Bourquin HC, Yancey LT. Addressing the cell phone-only problem: cell phone sampling vs address based sampling. Survey Practice, February 2009. Available online from.