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Recent Improvements for Dual-Frame RDD Sampling Methodology

Recent Improvements for Dual-Frame RDD Sampling Methodology. 29 th Annual Meeting March 26, 2012. Presentation Outline. Dual-Frame RDD: Sampling considerations Weighting considerations Areas of Improvement: The moving target for cellphone-only (CPO) households The evolving landline frame

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Recent Improvements for Dual-Frame RDD Sampling Methodology

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  1. Recent ImprovementsforDual-Frame RDD Sampling Methodology 29th Annual Meeting March 26, 2012

  2. Presentation Outline • Dual-Frame RDD: • Sampling considerations • Weighting considerations • Areas of Improvement: • The moving target for cellphone-only (CPO) households • The evolving landline frame • Solution: • Better quantification of CPO households • New landline frame to cover virtually all landline households

  3. Sampling Considerations • A representative sample mirrors its target population: • Geographic characteristics: state and counties • Demographic characteristics: gender, race, age, education, etc. • Behavioral characteristics: telephone status (CPO) • BRFSS sampling design is non-EPSEM: • Disproportionate stratified sampling (CSS) for landlines • Provisional mixture of cellular and landline households

  4. Weighting Considerations • Weights are needed to compensate for: • Differential selection probabilities (by design)  Design Weights • Differential nonresponse rates  Poststratified/Raked Weights • ACS/CPS estimates for geodemographic target totals • CDC estimates for CPO households • Cost of weighting: MSE = Variance + Bias2 Bias Standard Deviation

  5. Areas of Improvement • Growing/changing CPO households can lead to: • Sampling inefficiencies (particularly in small areas) • Weighting inconsistencies • Landline frame may leave out certain assignments: • Less systematic assignment of new numbers • New providers assign numbers outside of the frame

  6. Areas of Improvement(CPO Household) • Research community indebted to the CDC for CPO estimates: • Survey based • Available at the state level and certain smaller areas • Current CPO estimates are critical: • Efficient sample mixture • Effective weighting strategy • Eliminating the need for screening out dual-users

  7. Areas of Improvement(CPO Households)

  8. Areas of Improvement(Landline Frame) 1+Listed 0-Listed • Potential Undercoverage of 1+Listed Frame • Brick et al. (POQ, Vol. 59, 1995): Less than 4% • Fahimi et al. (POQ, Vol. 73, 2009): About 20% • Boyle et al. (POQ, Vol. 73, 2009): About 5% • Barron et al. (SP, April 2010): Between 7 to 14% • Weiss et al. (AAPOR 2011): 0-Listed can be more productive

  9. Areas of Improvement(Declining Listed Numbers)

  10. Solution(New Landline RDD Frame) • Traditional frame includes only 1+listed banks • Need a new frame that includes 1+assigned banks • Each bank will be indexed by its number of: • Listed assignments • Unlisted assignments • Can accommodate various sampling options: • K-Assigned RDD sampling, K 1 • True PPS with MOS = f (assignment density of banks)

  11. Solution(Counts of CPO Households at the County Level) • Obtain counts of telephone households (landline or cellular) for each county • Obtain counts of landline householdsin each county • Triangulate counts of CPO households for each of the 3,141 counties by: Telephone Households - Landline Households

  12. Solution(Distribution of Multi-line Households from BRFSS)

  13. Solution(Distribution of Landline Households by County)

  14. Solution(Counts of CPO Households at the County Level)

  15. Solution(Clark County Idaho is Mostly CPO) • Most 294 households serviced by Mud Lake Telephone Cooperative Association (MLTCA) • MLTCA provides Canopy Wireless Internet Service (CWIS) to residences and businesses • CWIS is a cost-effective alternative for broadband in areas where it is cost-prohibitive to upgrade the old wireline infrastructure

  16. Solution(More Efficient Sampling/Weighting Practices)

  17. Solution(More Efficient Sampling/Weighting Practices)

  18. Conclusions • Dual-frame RDD provides an effective alternative for probability-based sampling for scientific surveys: • Proper mixture of landline and cellular numbers • Efficient weighting using current CPO estimates • Quarterly estimates of CPO households at the county level will help states: • Higher quality survey estimates • Eliminate the need for expensive screening of dual users • A more comprehensive landline frame covers landline households with numbers outside of the 1+listed frame

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