Effects of Sampling and Screening Strategies in an RDD Survey Anthony M. Roman, Elizabeth Eggleston, Charles F. Turner, Susan M. Rogers, Rebecca Crow, Sylvia Tan What: RDD study conducted in Baltimore When: Sept – August 2009 Who: Target population: People aged Why: Measure risk behaviors and prevalence of 3 STI’s (Gonorrhea, Chlamydia and Trichonomiasis) RDD SAMPLE FRAME INEFFICIENT DUE TO AMOUNT OF CALLING REQUIRED TO SCREEN OUT NON- RESIDENTIAL TELEPHONE NUMBERS AND HOUSEHOLDS WITHOUT SOMEONE AGED CONCERN: High costs will require fewer completed interviews and lower power in statistical analyses REWORD ORIGINAL SCREENER QUESTION Original question: “How many people aged currently live in this household?” New screener questions: 1) 1)“How many people aged 36 or older currently live in this household?” 2) 2)“How many people aged currently live in this household?” Table 1: Results of Telephone Number Dialing by Stratum Rate ofRate at which Overall Connecting toHouseholds hadRate ResidentialAge EligibleColumn 1 x Sample Source:Households:Respondent:Column 2: Original RDD30.80%31.10%9.58% List with person List Age Unknown Combined lists and RDD with lists removed ** The dual frame design resulted in a 31% increase in dialing efficiency and a relevant decrease in survey cost. Additional increase in efficiency can be realized with higher reliance on the lists. List assisted RDD sample (GENESYS) Address matching for advance letters Phone interviewers screen for eligibility: Age Live in city of Baltimore Speak English Have touch-tone phone Parental permission when required Random selection of eligible respondent within household TACASI interview $20 for minute interview Additional $40 for providing urine specimen by mail BACKGROUND ORIGINAL DESIGN ATTEMPTED SOLUTION PROBLEM 1: ELIGIBILITY RATE Based on census estimates, lower than expected rate of households with someone aged (21.3% vs. 31.6%) Concern: Bias caused by missing households, cell phone only households, higher costs due to lower eligibility rates RESULT Wording change produced rate of 31.3% of households with someone aged15-35 CLOSELY CORRESPONDS WITH CENSUS ESTIMATE! ATTEMPTED SOLUTION MOVE TO DUAL-FRAME SAMPLE USING COMBINATION OF LISTS & RDD Four strata within sample frame: 1) 1)List households believed to have someone aged ) 2)List households believed NOT to have someone aged ) 3)List households with no age information on occupants 4) 4)RDD sample with all list households removed Sampling from strata at different rates, all households in Baltimore can exist in one and only one stratum, all probabilities of selection known. PROBLEM 2: COST PROBLEM 3: GETTING ELIGIBLE RESPONDENT ON PHONE Age group is known to spend less time at home  talking to eligible respondent requires many call attempts Concerns: 1) Extra call attempts = higher cost; 2) Inability to EVER get some respondents = lower response rates ATTEMPTED SOLUTION ALTER METHOD OF RANDOM SELECTION OF ELIGIBLE RESPONDENT Original method: 1/n for each of n eligible people within household New method: Increased probability of selection for person who answered screener questions if that person is eligible themselves Screener respondent has 2/(n+1) chance of selection All other eligible people in household 1/(n+1) chance Example: 2 eligible people in household and screener respondent one of them  Original method gave this person ½ chance of selection  New method gave screener respondent 2/3 chance and other eligible 1/3 chance NET RESULTS DECREASED EFFORT = INCREASED SAVINGS; INCREASED RESPONSE RATE BEFORE MODIFICATIONSAFTER MODIFICATIONSRESULTS 4.64 interviewer hours per complete interview 4.15 interviewer hours per complete interview  10.6% reduction in interviewer effort  Comparable reduction in data collection costs  Additional savings can be gained with higher reliance on lists in future sample Table 3: Response rate changes due to sampling modifications InterviewAgreed to receiveReturned Response Rate:Specimen Kit:Specimen: Original design55.04%84.20%78.26% After modifications ) 1) The increased response rate among identified eligible respondents from 55% to 59.7% we assume to be due to: Selecting screener respondents more often meant getting more interviews A higher % of households received advance letters due to lists Lists produced slightly higher response rates 2) Increased agreement to receive specimen cup due to selecting more screener respondents as they had an increased rapport with interviewers and agreed more often. 3) The increased rate of returning cups was due to one last modification and that was offering $100 instead of $40 to those who initially agreed to send in a cup and then failed to do so. NEXT STEPS Examine effects of sample design modifications on: Survey weights Estimated standard errors Use results to optimize sampling fractions across strata RESULT RESULTS Original method: averaged call attempts per interview. New Method: averaged 8.88 call attempts per interview. **27.9% reduction in call attempts with relevant cost savings *ACS = American Community Survey Distributions of Respondent Characteristics