NLS Listening Sessions Handout - International Surveys

Thank you for your willingness to contribute to our listening session, which is part of an effort to plan
for a potential NLSY26 cohort. We have provided a few topics and background information to help get
your thoughts flowing before your session.
Example questions to help you brainstorm before attending the listening session
• How frequently does the survey that you work on collect data from sample members?
• Have you incorporated administrative data sets into your survey? What administrative data are
you bringing in?
• What paradata do you collect?
• What approaches do you take to try to maintain high response rates in your longitudinal survey?
• Does your survey oversample certain populations?
• What meta data standards (for example, DDI lifecycle or Dublin core) does your survey employ
for their data products?
Past feedback BLS already received from other stakeholders for a new youth cohort
1. General themes from outreach that BLS conducted with Federal agencies and departments.
• Methodological feedback
o Administering different modules via text, web or other mode at irregular or more frequent
intervals.
 Modules could be triggered by current events.
o Two-stage sample
 A large sample would have minimal survey collection while a smaller segment of
the sample would support detailed survey questions and experiments.
• Measurement feedback
o Machine learning to create measures.
o Including experiments in the survey.
o Consider use of cell-phone tracking and wearables.
o Collecting bio-samples.
• Alternative data sources feedback
o Alternative data sources could be useful in a range of domains including crime,
education, health, social services, and income/employment.
o These sources can provide information about conditions prior to survey (e.g., birthweight
and health for youth; income and social program participation for their parents).
o Any new survey should plan for linkages through early consideration of the PII data
requirements (Social Security Number, for example).