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Address Frames and Mail Surveys as Complements (or Alternatives) to RDD Surveys

Address Frames and Mail Surveys as Complements (or Alternatives) to RDD Surveys. Michael W. Link, Michael P. Battaglia, Martin R. Frankel, Larry Osborn, and Ali H. Mokdad . Second International Conference on Telephone Survey Methodology, Miami, FL . Problems Facing RDD Surveys.

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Address Frames and Mail Surveys as Complements (or Alternatives) to RDD Surveys

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  1. Address Frames and Mail Surveysas Complements (or Alternatives)to RDD Surveys Michael W. Link, Michael P. Battaglia, Martin R. Frankel, Larry Osborn, and Ali H. Mokdad Second International Conference on Telephone Survey Methodology, Miami, FL

  2. Problems Facing RDD Surveys • Growing Nonresponse • Frame coverage issues: • Households with no telephones (1.6%) • Cell phone only households (3.7%) • Households in zero-banks (3-4%) • Frame efficiency issues: • Proliferation of telephone numbers • Cell phone numbers in mixed-use exchanges • Other issues: • Erosion of geographic specificity at state and substate levels

  3. Behavioral Risk Factor Surveillance System (BRFSS) • Monthly state-based RDD survey of health issues • 50 states, District of Columbia, Puerto Rico, Guam, and Virgin Islands • 300,000 adult interviews conducted in 2005 • Faced with declining response rates • Need to identify best future design (frame & mode)

  4. UNITED STATES POSTAL SERVICE KIPKE BOB GRAPHICS KIPKE BOB GRAPHICS 2000 2001 USPS Delivery Sequence File (DSF) as an alternative sampling frame • File contains • All delivery point addresses serviced by USPS • Identifies address type • Residential vs business • City style vs PO box vs other types • Format conforms to USPS addressing standards • Initial assessments for survey use: • Highest coverage in urban areas • Potential for coverage to improve in rural areas

  5. Potential Drawbacks of DSF • Unknown level of coverage: • Excludes households with no USPS mail delivery • Must purchase through list vendor (not USPS) • Updates/list maintenance may vary • Some exclude addresses on request • Includes simplified addresses: • City, state, zip code only • Other potential problems: • Seasonal units, PO Boxes and multi-drop addresses

  6. MAIL Bob's.ppt http://www.geocities.com/bkip20002/index.html Copyright 2002 -All Rights Reserved- Key questions to address • How do RDD and DSF-based mail surveys compare in terms of: • frame efficiency • response rates • respondent demographics • Estimates on key health issues • Can DSF-based mail surveys reach households without telephones and cell phone-only households?

  7. BRFSS 2005 DSF mail survey pilot • Six states: CA, IL, NJ, NC, TX, WA • Sampling frame: access to Delivery Sequence File (DSF) provided by Marketing Systems Group • Mode: mail survey with telephone verification for respondent selection • Mail survey fielded March 15-May 15, 2005 • Compared to monthly RDD surveys from March-May, 2005

  8. BRFSS 2005 DSF pilot: sample design • Probability sample from DSF household frames in each state • Excluded business addresses identified by USPS or Marketing Systems Group • Included seasonal units, vacant units, PO Boxes, throwback units, and drop point units • Stratified each state sample by county and address type • Drew 1,680 addresses per state using systematic random sampling

  9. Split sample treatment groups • Postcard (after 7 days) • Second questionnaire mailing (after 2 weeks) • Surname on address label • Alternative within household selection methods: • any adult (non-probability) • next birthday • all adults

  10. Frame coverage assessment and characteristics

  11. Percentage of Counties with >10% Under-coverage by State % counties with >10% under-coverage NJ CA IL WA TX NC

  12. Percentage of Counties with >10% Under-coverage by Pct. Urban % counties with >10% under-coverage 25-49% 50-74% 75+% < 25% % of adults in county living in urban area

  13. BRFSS DSF Pilot:Types of Addresses

  14. Response rates

  15. Design factors and probability of completed interview from total cases(adjusted odds ratios)

  16. Comparison of RDD telephone and DSF mail survey response rates

  17. Within household selection

  18. Comparison of “Equalized” Weighted Gender Distributions: % Female

  19. Other demographics of DSF mail survey respondents

  20. Percent some college or more 71.8 58.4 53.8

  21. Percent white 69.5 67.7 64.9

  22. Percent household income > $50,000 48.6 46.4 43.8

  23. Comparison of Survey Estimates

  24. Comparison of Survey Estimates Significance: * p<.05, ** p<.01, *** p < .001 Note: Data weighted for sample design and post-stratified to sex-age totals for each state. Final weights were ratio adjusted to equalize the number of cases across states. Logistic regression models adjusted for state of residence, sex, race, age, education, and having health care coverage.

  25. Reaching cell-only andnon-telephone households

  26. Type of householdtelephone access 1 Based on interviews NHIS conducted July – December, 2004. Source: Stephen J.Blumberg, Julian V. Luke, and Marcie L. Cynamon (2005). “The Prevalence and Impact of Wireless Substitution: Updated Data from the 2004 National Health Interview Survey.” Presented at the 2005 American Association for Public Opinion Research Annual Conference, Miami Beach, FL.

  27. Effect of household telephone access on mail survey estimates Figures are adjusted odds ratios. Significance: * p<.05, ** p<.01, *** p < .001 Note: Data weighted for sample design and post-stratified to sex-age totals for each state. Final weights were ratio adjusted to equalize the number of cases across states. Logistic regression models adjusted for state of residence, sex, race, age, education, and having health care coverage.

  28. Advantagesof address-based design • In low response rate states the address-based mail survey approach can yield response rates similar to RDD rates • Telephone follow-up of non-respondents should raise rates • Approach reaches households without land-line telephones • Weighted prevalence estimates were similar for 5 of 8 risk factors • Facilitates geocoding and mapping

  29. Disadvantagesof address-based design • Coverage in rural areas is a potential problem • Mail survey limits number of questions and complexity of survey • Mail survey alone does not yield higher response rates than RDD • Less control over within household selection • Mail survey respondents tend to have higher SES

  30. Next Steps • 2006 “production level” pilot study in 6 states • Test alternative sampling approaches: • RDD sample reverse-matched for addresses • Address-based sample matched for telephone numbers • Test mixed-mode design: • If address available: mail survey with telephone follow-up of nonrespondents • If no address available: telephone survey

  31. Contact:Michael LinkMLink@cdc.govwww.cdc.gov/brfss

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