Summary
The Annual Gadgets Survey, sponsored by the Pew Internet and American Life Project, obtained telephone interviews – both landline and cell phone – with a nationally representative sample of 2,054 adults living in the continental United States. The survey was conducted by Princeton Survey Research International. The interviews were conducted in English by Princeton Data Source, LLC from October 24 to December 2, 2007. Statistical results are weighted to correct known demographic discrepancies. The margin of sampling error for the complete set of weighted data is ±2.4%. Details on the design, execution and analysis of the survey are discussed below.
Design and Data Collection Procedures
» Sample Design
A combination of landline and cellular random digit dial (RDD) samples was used to represent all adults in the continental United States who have access to either a landline or cellular telephone. Both samples were provided by Survey Sampling International, LLC (SSI) according to PSRAI specifications.
Random phone numbers for the landline sample were generated from active blocks (area code + exchange + two-digit block number) that contained three or more residential directory listings. Active blocks were chosen with probabilities in proportion to their share of listed telephone households. The cellular sample was not list-assisted, but was drawn through a systematic sampling from 1000-blocks dedicated to cellular service according to the Telcordia database.
» Contact Procedures
Interviews were conducted from October 24 to December 2, 2007. As many as 10 attempts were made to contact every sampled telephone number. Sample was released for interviewing in replicates, which are representative subsamples of the larger sample. Using replicates to control the release of sample ensures that complete call procedures are followed for the entire sample. Calls were staggered over times of day and days of the week to maximize the chance of making contact with potential respondents. Each household received at least one daytime call in an attempt to find someone at home.
For the landline sample, interviewers asked to speak with the youngest adult male currently at home. If no male was available, interviewers asked to speak with the youngest female at home. This systematic respondent selection technique has been shown to produce samples that closely mirror the population in terms of age and gender.
For the cellular sample, interviews were conducted with the person who answered the phone. Interviewers verified that the person was an adult and in a safe place before administering the survey. If this person was not an adult, they were screened out as ineligible. Cellular sample respondents were offered a post-paid cash incentive for their participation.
Weighting and analysis
Weighting is generally used in survey analysis to compensate for sample designs and patterns of non-response that might bias results. A two-stage weighting procedure was used to weight this dual-frame sample. A first-stage weight of 0.5 was applied to all dual-users to account for the fact that they were included in both sample frames.4 landline respondents who have a working cell phone, or [b] cell phone respondents who have a regular land line phone where they currently live.] All other cases were given a first-stage weight of 1.0. The second stage of weighting balanced sample demographics to population parameters. The sample was balanced to match national population parameters for sex, age, education, race, Hispanic origin, region (U.S. Census definitions), population density, and telephone usage. The White, non-Hispanic subgroup was also balanced on age, education and region. The basic weighting parameters came from a special analysis of the Census Bureau’s 2006 Annual Social and Economic Supplement (ASEC) that included all households in the continental United States that had a telephone. The cell phone usage parameter came from an analysis of the July-December 2006 National Health Interview Survey.
Weighting was accomplished using Sample Balancing, a special iterative sample weighting program that simultaneously balances the distributions of all variables using a statistical technique called the Deming Algorithm. Weights were trimmed to prevent individual interviews from having too much influence on the final results. The use of these weights in statistical analysis ensures that the demographic characteristics of the sample closely approximate the demographic characteristics of the national population.
