Recent Improvements for Dual-Frame RDD Sampling Methodology 29 th Annual Meeting March 26, 2012

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

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

4 Weighting Considerations Weights are needed to compensate for: Weights are needed to compensate for: Differential selection probabilities (by design) Design Weights Differential selection probabilities (by design) Design Weights Differential nonresponse rates Poststratified/Raked Weights Differential nonresponse rates Poststratified/Raked Weights ACS/CPS estimates for geodemographic target totals ACS/CPS estimates for geodemographic target totals CDC estimates for CPO households CDC estimates for CPO households Cost of weighting: Cost of weighting: Bias Standard Deviation MSE = Variance + Bias 2

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

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

7 Areas of Improvement (CPO Households)

8 Areas of Improvement (Landline Frame) 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 1+Listed 0-Listed

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 Listed assignments Unlisted assignments Unlisted assignments Can accommodate various sampling options: K -Assigned RDD sampling, K 1 K -Assigned RDD sampling, K 1 True PPS with MOS = f (assignment density of banks) True PPS with MOS = f (assignment density of banks)

11 Solution (Counts of CPO Households at the County Level) telephone households Obtain counts of telephone households (landline or cellular) for each county landline households Obtain counts of landline households in 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) Most 294 households serviced by Mud Lake Telephone Cooperative Association (MLTCA) MLTCA provides Canopy Wireless Internet Service (CWIS) to residences and businesses 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 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)

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

19 Contact