Is It Necessary to Reimburse Cellphone Respondents?
Appendix D: About the Surveys
The analysis in this report is based on telephone interviews conducted February 18-22, March 25-29 and May 12-18, 2015 among a combined national sample of 5,006 adults, ages 18 or older, living in all 50 U.S. states and the District of Columbia (1,751 respondents were interviewed on a landline telephone, and 3,255 were interviewed on a cellphone, including 1,876 who had no landline telephone). The data in this report focuses on the cellphone respondents. The surveys were conducted by interviewers at Princeton Data Source under the direction of Princeton Survey Research Associates International. A combination of landline and cellphone random digit dial samples were used; both samples were provided by Survey Sampling International. Interviews were conducted in English and Spanish. Respondents in the landline sample were selected by randomly asking for the youngest adult male or female who is now at home. Interviews in the cell sample were conducted with the person who answered the phone, if that person was an adult age 18 or older. For detailed information about our survey methodology, see http://www.pewresearch.org/methodology/u-s-survey-research/
The landline and cellphone sample for each poll are weighted using an iterative technique that matches gender, age, education, race, Hispanic origin and nativity and region to parameters from the 2013 Census Bureau’s American Community Survey and population density to parameters from the Decennial Census. The sample also is weighted to match current patterns of telephone status (landline only, cellphone only, or both landline and cellphone), based on extrapolations from the 2014 National Health Interview Survey. The weighting procedure also accounts for the fact that respondents with both landline and cellphones have a greater probability of being included in the combined sample and adjusts for household size among respondents with a landline phone. The margins of error reported and statistical tests of significance are adjusted to account for the survey’s design effect, a measure of how much efficiency is lost from the weighting procedures.
The following table shows the unweighted sample sizes and the error attributable to sampling that would be expected at the 95% level of confidence for different groups in the survey:
Sample sizes and sampling errors for other subgroups are available upon request.
In addition to sampling error, one should bear in mind that question wording and practical difficulties in conducting surveys can introduce error or bias into the findings of opinion polls.