Generation Next Survey, 2006
SummaryFeaturing an oversample of members of "Generation Next" (young adults ages 18-25), this Pew survey examines this generation's outlook, lifestyle, and politics. Respondents were asked to compare their own generation to others in several areas including opportunities, challenges, and lifestyle choices. Other topics covered include technology usage, news consumption, political attitudes and behavior, and personal aspirations. Religion variables include religious affiliation, church attendance, and the importance of spirituality.
The ARDA has added six additional variables to the original data set to enhance the users' experience on our site.
Data FileCases: 1501
Weight Variable: WEIGHT
The data were weighted using demographic weighting parameters derived from the March 2005 Census Bureau's Current Population Survey, along with estimates of current patterns of telephone status in the U.S., using an iterative technique that simultaneously balances the distributions of all weighting parameters.
Data CollectionSeptember 6-October 2, 2006
Funded ByThe Pew Research Center
Collection ProceduresInterviewing for the survey was conducted by telephone Sept. 6-Oct. 2, 2006 among a 1,501 adults ages 18 and older, including an oversample of members of Generation Next (ages 18-25). The total sample size for those 18-25 is 579, including 250 interviews conducted by cell phone; 130 of these individuals had no landline phone. In order to compensate cell phone respondents for any toll charges incurred, those interviewed by cell phone were offered an incentive of $10 for completing the survey. Interviewing was conducted by the research firm Schulman, Ronca & Bucuvalas, Inc. (SRBI). The samples were prepared by Survey Sampling International (SSI).
Sampling ProceduresThe sample for a typical national survey consists of a random digit sample of telephone numbers selected from telephone exchanges in the continental United States. The random digit aspect of the sample is used to avoid "listing" bias and provides representation of both listed and unlisted numbers (including not-yet-listed). The design of the sample ensures this representation by random generation of the last two digits of telephone numbers selected on the basis of their area code, telephone exchange, and bank number.
The telephone exchanges are selected with probabilities proportional to their size. The first eight digits of the sampled telephone numbers (area code, telephone exchange, bank number) are selected to be proportionally stratified by county and by telephone exchange within county. That is, the number of telephone numbers randomly sampled from within a given county is proportional to that county's share of telephone numbers in the U.S. Only working banks of telephone numbers are selected. A working bank is defined as 100 contiguous telephone numbers containing one or more residential listings.
The sample is released for interviewing in replicates. Using replicates to control the release of sample to the field ensures that the complete call procedures are followed for the entire sample. The use of replicates also ensures that the regional distribution of numbers called is appropriate. Again, this works to increase the representativeness of the sample.
As many as 10 attempts are made to complete an interview at every sampled telephone number. The calls are staggered over times of day and days of the week to maximize the chances of making a contact with a potential respondent. All interview breakoffs and refusals are re-contacted at least once in order to attempt to convert them to completed interviews. In each contacted household, interviewers ask to speak with " the youngest male, 18 years of age or older, who is now at home." If there is no eligible man at home, interviewers ask to speak with "the youngest female, 18 years of age or older, who is now at home." This systematic respondent selection technique has been shown empirically to produce samples that closely mirror the population in terms of age and gender.
Non-response in telephone interview surveys produces some known biases in survey-derived estimates because participation tends to vary for different subgroups of the population, and these subgroups are likely to vary also on questions of substantive interest. In order to compensate for these known biases, the sample data are weighted in analysis.