Recent Improvementsfor

Dual-Frame RDD Sampling Methodology

29th Annual MeetingMarch 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:

2

1

1

2

2)]([1

n

iii

n

iii

wn

wnn

wcvUWEB

ias

Standard Deviation

MSE = Variance + Bias2

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)

ALARAZCACOCTDCDEFLGAIAIDILINKSKYLAMAMDMEMIMNMOMSMTNCNDNENHNJNMNVNYOHOKORPAPWSCSDTNTXUTVAVTWAWIWVWY

CDC-07 CDC-10

8

Areas of Improvement(Landline Frame)

Available Landlines 100-Series Banks (NPA-NXX-XX00 – NPA-NXX-XX99)

2.9M

1.9M

4.3M

0.7M

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)

2005 2007 2009 2010-10 2011-01 2011-04 2011-10

76,923,90374,518,722

72,578,043

67,739,38465,751,221 64,781,241

62,396,939

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 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)

AK AR CA CT DEGA HI ID IN KY

MA MEMN MS NC NE NJ

NV OH OR PR SC TN UT VIW

AW

V0.0%

1.5%

3.0%

4.5%

Urban SuburbanRural

13

Solution(Distribution of Landline Households by

County)

14

Solution(Counts of CPO Households at the County

Level)

1 31410%

20%

40%

60%

80%

100%

US Counties (1 to 3141)

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)

WY

WV WI

VT

VAVATXTXTXTXTNTNSD SCPAOKOKOHNY

NM NENE

NDNC

MT

MS

MO

MO

MN MI

MI

MALAKYKYKS IN IN IL ID IA IA GAGA FL

COCAAZ

ARAL

0%

50%

100%(CPO Households by County and State)

County-CPO State-CPO

17

Solution(More Efficient Sampling/Weighting Practices)

CT

NH

VT

DE

MA

LA

PA IA PA

AL IN WI

NJ

KS

MN

WV

MD

OK

SD MI

KY

AK

NC

ME

GA IL TN

MO

VA

CA

CO

OH

WA FL

NE

MT

SC

NY

ND

MS

AR

UT

OR

NV HI

TX

AZ

NM ID DC

WY

0%

10%

20%

30%

40%

50%

CDC-07 CDC-10 MSG-12

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

19

Contact