RDD Surveys Research Articles

多人数質問調査法の現在（2）―電話調査と RDD の問題点―:カバレッジ・エラーとノンレスポンス・エラーへの対応

多人数質問調査法の現在（2）―電話調査と RDD の問題点―:カバレッジ・エラーとノンレスポンス・エラーへの対応

Current State of RDD Surveys and Challenges Ahead

Current State of RDD Surveys and Challenges Ahead

固定電話と携帯電話を対象とした電話調査の導入と推定値の評価

固定電話と携帯電話を対象とした電話調査の導入と推定値の評価

Landline and Cell Phone Response Measures in Behavioral Risk Factor Surveillance System

Landline RDD surveys are facing a coverage problem due to increasing cell phone only households in the US. To address this issue, the Behavioral Risk Factor Surveillance System (BRFSS) included cell phone samples in 2009. BRFSS landline and cell phone data for 2009 were used to examine the differences between landline and cell phone data in several response measures, which included: response and cooperation rates, percent completed screening question, percent completed interview and percent refusal/break-off the interview. The completion rates and refusal/break-off rates are estimated overall and among those completed screening questions, for the total sample and by state. Cell phone samples were less likely to be answered than landline samples. The dispositions of cell phone calls were more likely to be noted as answering devices/voicemail, no response or refusal/break-offs. Cell phone respondents were also less likely to complete screening questions. However, among respondents who completed screening questions, cell phone respondents were more likely to complete the survey and less likely to refuse or break-off, a pattern which was noted in the majority of states. Also, response and cooperation rates show different pictures in the landline and cell phone samples, where landlines had higher response rate than cell phones, and cell phones had higher cooperation rates than landlines. The results provide valuable information on the importance of pursuing better strategies to overcome barriers to higher completion of screening questions and success at the initial stage of the interview. Such effects could improve the overall response rate and under coverage bias in the landline.

The growing challenge of wireless telephones to RDD surveys : Some U.S. findings

The growing challenge of wireless telephones to RDD surveys : Some U.S. findings

A Turn Toward Avoidance? Selective Exposure to Online Political Information, 2004–2008

Scholars warn that avoidance of attitude-discrepant political information is becoming increasingly common due in part to an ideologically fragmented online news environment that allows individuals to systematically eschew contact with ideas that differ from their own. Data collected over a series of national RDD surveys conducted between 2004 and 2008 challenge this assertion, demonstrating that Americans’ use of attitude-consistent political sources is positively correlated with use of more attitudinally challenging sources. This pattern holds over time and across different types of online outlets, and applies even among those most strongly committed to their political ideology, although the relationship is weaker for this group. Implications for these findings are discussed.

Fruit and Vegetable Intake of US Adults: Comparing Intake by Mode of Survey Administration

Modes for collecting dietary data vary across studies and include in-person/interviewer-administered surveys, mail, and telephone surveys. Few studies use mixed modes to assess dietary intakes. Using data from the 2007 Health Information National Trends Survey, we compared fruit and vegetable intake of adults measured through dual modes (mail and random-digit dial [RDD] telephone), and discussed potential factors that could account for mode differences. The Health Information National Trends Survey data were collected through mailed (n=3,582), and RDD (n=4,092) surveys from December 2007 to May 2008. Data were weighted and analyzed in SUDAAN. Unadjusted mean fruit and vegetable intake was 0.48 servings higher ( P<0.001) among mail (mean 5.40) vs RDD (mean 4.09) participants. In a multivariate model that controlled for other predictors, the odds of consuming ≥5 servings of fruit and vegetables per day was 83% higher among mail respondents compared to RDD (odds ratio 1.83, 95% confidence interval 1.62 to 2.07). Other predictors of fruit and vegetable intake were sex, education, participation in physical activity, self-rated health, and knowledge of the fruit and vegetable recommendation. Methodologic issues may account for modal differences in fruit and vegetable intake. Different measures (cups, servings) were used to assess fruit and vegetable intake in both modes, details about portion sizes were provided on the mail mode vs RDD, and closed-ended responses were provided on the mail vs open-ended responses for RDD. We cannot recommend one mode over the other nor attribute mode differences to real differences in reported fruit and vegetable intake between participants from both modes. Future research that uses dual modes needs to use identical methods of dietary assessment to minimize these potential sources of error. Further research is needed to validate the use of dual modes to assess dietary intake and inform research practice.

Address-Based Sampling for Subpopulation Surveys

In this article, we describe the use of address-based sampling (ABS) for conducting a mail survey of a subgroup. Although ABS has been investigated as an alternative household sampling frame, its use for sampling subgroups is limited. Some researchers have used ABS to select households but then recruit households by telephone to the extent possible to screen for members of the subgroup. The approach we describe uses a two-phase methodology with mail as the primary mode of recruitment and data collection for all households. Facing declining response and coverage rates in its landline RDD surveys, the National Household Education Surveys (NHES) program embarked on a redesign effort. The two-phase ABS design using mail as the primary mode of data collection was chosen for the NHES:2009 Pilot Study. In the first phase, all sampled households were mailed a screener that identified members of the eligible subgroup (children) and provided the data needed for sampling among them. A second-phase substantive questionnaire was mailed to the sampled members of the subgroup. This use of the ABS and mail as the primary mode of data collection is new and largely untested. The findings from the NHES Pilot Study revealed that this approach is a feasible alternative for surveying targeted subgroups. Although the methods must undergo more robust and rigorous tests, it is an approach that may be able to fill some of the void created by the low response and coverage rates that afflict RDD surveys.

Cell-Phone-Only Voters in the 2008 Exit Poll and Implications for Future Noncoverage Bias

Amid growing concern about potential noncoverage bias in random digit dial survey samples that exclude cell phones, a national face-to-face exit poll provided an opportunity to reach November 2008 Election Day voters regardless of telephone status and to evaluate how the cell-only subgroup has changed since the 2004 election. The National Election Pool's survey found a sharp increase in cell-only incidence, comparable to trends for the general public in government surveys, with cell-only status approaching the norm for voters under age 30. But voters age 30 and older actually abandoned landlines at a faster rate, and the difference in presidential vote preference between the cell-only and landline-accessible voters in this age group was even greater than for younger voters. This suggests that typical poststratification weighting adjustments for age may be less likely to mitigate noncoverage bias in future landline-only RDD surveys.

Improving Standard Poststratification Techniques For Random-Digit-Dialing Telephone Surveys

Random-digit-dialing surveys in the United States such as the Behavioral Risk Factor Surveillance System (BRFSS) typically poststratify on age, gender and race/ethnicity using control totals from an appropriate source such as the 2000 Census, the Current Population Survey, or the American Community Survey. Using logistic regression and interaction detection software we identified key effect socio-demographic variables and important two-factor interactions associated with several health risk factor outcomes measured in the BRFSS, one of the largest annual RDD surveys in the United States. A procedure was developed to construct control totals, which were consistent with estimates of age, gender, and race/ethnicity obtained from a commercial source and distributions of other demographic variables from the Current Population Survey. Raking was used to incorporate main effects and two-factor interaction margins into the weighting of the BRFSS survey data. The resulting risk factor estimates were then compared with those based on the current BRFSS weighting methodology and mean squared error estimates were developed. The research demonstrates that by identifying socio-demographic variables associated with key outcome variables and including these variables in the weighting methodology, nonresponse bias can be substantially reduced.

面接調査の現状と課題

THE YOMIURI SHIMBUN has conducted monthly public opinion polls, using face-to-face interviews, since March 1978. Since the beginning of the 1990s, the response rate to these surveys has been decreasing, and is remarkably low in recent days. Since 2006, the average yearly response rate has been under 60%.I believe the main reason for the decline is increasing awareness of personal privacy. As evidence of this, there has been a greater rise in the percentage of people who decline to participate, than in the percentage of those who are not at home when interviewers visit. We have taken steps to improve the situation, such as hiring skilled interviewers, but it has not stopped the decline. At this moment, we do not have a sure-fire method for improving the rate of response.The current fashion is for RDD surveys, and if face-to-face interviews are to survive, I believe we must increase understanding of the importance of opinion polls. To that end, in addition to further improving the implementation of our surveys, we should make every effort to prepare fair-minded questions, analyze and report survey results appropriately and make data available to the public.

Evaluating the Effects of Screening for Telephone Service in Dual Frame RDD Surveys

The high costs and largely unknown error properties of cellular telephone interviews make screening for cell-only adults a potentially attractive option in dual frame RDD surveys. Screening out adults with landline telephones from the cellular sample does not affect the coverage properties of a dual frame survey, but it may affect other sources of error, especially nonresponse. In this study, data from a 2006 dual frame RDD survey conducted for the Pew Research Center, the Associated Press, and AOL are used to evaluate the effects of implementing a cell-only screener on both the bias and variance of weighted survey estimates. The effect of screening appears to be minimal so long as an adjustment for telephone service is included in the weighting method. Results of an attempt to correct for residual nonresponse due to inaccessibility are also discussed.

What's Missing from National Landline RDD Surveys?: The Impact of the Growing Cell-Only Population

The number of cell phone only households has continued to grow - 12.8 percent of all households by the end of 2006, according to the National Health Interview Survey (NHIS). To assess the extent and nature of the potential bias in landline telephone samples created by the absence of cell-only households, the Pew Research Center conducted four independent dual frame studies in 2006, three of which included at least 200 interviews with cell-only respondents. Despite the fact that there are significant differences between cell-only and landline respondents on many important variables, across the four surveys with different substantive content we find that including a cell-only sample with a landline RDD sample produces general population estimates that are nearly identical to those from the landline sample alone. Yet, while the noncoverage problem is currently not damaging estimates for the entire population, we find evidence that it does create biased estimates on certain variables for young adults, 25 percent of whome are cell-only according to the most recent government estimate.

Leaving Answering Machine Messages: Do they Increase Response Rates for RDD Surveys?

Leaving Answering Machine Messages: Do they Increase Response Rates for RDD Surveys?

Telephone Survey Methodology.

SECTION A: COVERAGE OF THE HOUSEHOLD POPULATION BY TELEPHONES.An Overview of Telephone Coverage (J. Massey). International Comparisons of Telephone Coverage (D. Trewin & G. Lee). Trends in the United States Telephone Coverage Across Time and Subgroups (O. Thornberry & J. Massey). Within--Household Coverage in RDD Surveys (D. Maklan & J. Waksberg). SECTION B: SAMPLING FOR TELEPHONE SURVEYS. Telephone Sampling Methods in the United States (J. Lepkowski). Implementing the Mitofsky--Waksberg Sampling Design with Accelerated Sequential Replacement (G. Burkheimer & J. Levinsohn). Cutoff Rules for Secondary Calling in a Random Digit Dailing Survey (C. Alexander). Minimum Cost Sample Allocation for Mitofsky--Waksberg Random Digit Dialing (R. Mason & F. Immerman).Weighting Adjustments for Random Digit Dialed Surveys (J. Massey & S. Botman).Stratification of Prefix Areas for Sampling Rare Populations (L. Mohadjer). Sampling Variance and Nonresponse Rates in Dual Frame, Mixed Mode Surveys (M. Sirken & R. Casady). SECTION C: NONRESPONSE IN TELEPHONE SURVEYS. An Overview of Nonresponse Issues in Telephone Surveys (R. Groves & L. Lyberg).Nonresponse: The UK Experience (M. Collins, et al.). Nonresponse Issues in Government Telephone Surveys (J. Drew, et al.). Survey Period Length, Unanswered Numbers, and Nonresponse in Telephone Surveys (J. Sebold). Effects of Interviewer Vocal Characteristics on Nonresponse (L. Oksenberg & C. Cannell). SECTION D: DATA QUALITY IN TELEPHONE SURVEYS.Measuring Data Quality (P. Biemer). Data Quality in Telephone and Face to Face Surveys: A Comparative Meta--Analysis (E. de Leeuw & J. van der Zouwen). Effects of Mode of Interview: Experiments in the UK (W. Sykes & M. Collins). A Comparison of Response Effects in Self--Administered and Telephone Surveys (G. Bishop, et al.). The Quality of Income Information in Telephone and Face to Face Surveys (E. Kormendi).Searching for Causes of Interviewer Effects in Telephone Surveys (L. Stokes & M.--Y. Yeh). SECTION E: COMPUTER--ASSISTED TELEPHONE INTERVIEWING. Computer--Assisted Telephone Interviewing: A General Introduction (W. Nicholls). The Design of CATI Systems: A Review of Current Practice (R. Baker & W. Lefes). Call Scheduling with CATI: Current Capabilities and Methods (M. Weeks). Questionnaire Design for CATI: Design Objectives and Methods (C. House & W. Nicholls). The Effects of CATI on Costs and Data Quality: A Comparison of CATI and Paper Methods in Centralized Interviewing (G. Catlin & S. Ingram). SECTION F: ADMINISTRATION OF TELEPHONE SURVEYS. Introduction: Administration of Telephone Surveys (L. Lyberg).Administrative Designs for Centralized Telephone Survey Centers: Implications of the Transition to CATI (S. Berry & D. O'Rourke). Observation of Behavior in Telephone Interviews (C. Cannell & L. Oksenberg). A Comparison of Centralized CATI Facilities for an Agricultural Labor Survey (R. Bass & R. Tortora). Administrative Issues in Mixed Mode Surveys (D. Dillman & J. Tarnai).Bibliography of Telephone Survey Methodology. Index.

Random Digit Dialing: A Comparison to Personal Surveys

Random Digit Dialing: A Comparison to Personal Surveys