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Using Paradata for Production Monitoring of the National Survey of Family Growth

Using Paradata for Production Monitoring of the National Survey of Family Growth. Nicole Kirgis and Bob Groves University of Michigan Survey Research Center March 2007. NSFG Cycle 7. Cross-sectional study of people 15-44 Cycle 7 began in June 2006 New quarterly sample rotation schedule

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Using Paradata for Production Monitoring of the National Survey of Family Growth

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  1. Using Paradata for Production Monitoring of the National Survey of Family Growth Nicole Kirgis and Bob Groves University of Michigan Survey Research Center March 2007

  2. NSFG Cycle 7 • Cross-sectional study of people 15-44 • Cycle 7 began in June 2006 • New quarterly sample rotation schedule • Sample is worked for 12-week quarters • Continuous data collection design • Sample areas are rotated in and out of the study each year.

  3. Importance of Paradata for NSFG • Understanding the work pattern of quarterly sample. • Monitoring efficiency compared to Cycle 6. • Given 12-week schedule, ability to make quick management decisions to change course.

  4. Three Basic Concepts for Paradata Review Daily and Quarterly Patterns of: 1. Effort 2. Active Sample 3. Productivity

  5. NSFG Data Structure Use daily incoming information on: • Interviewers • Sample segments • Housing Units • Calls • Contacts • Respondents

  6. The NSFG Dashboard Effort Active Sample Productivity % occupied interviews hours % eligible response rate targeting % production % nonworked calls/interview calls mean calls hours/interview % peak calls % locked bldgs trends in key indicators ratio: screener/ main calls % 8+ calls mean propensity by sexual activity judgment % resistant % hard appt. mean propensity Exit

  7. Paradata Next Steps • Ongoing enrichment of paradata. • Better predict ebb and flow of work each year. • Continuous improvement of continuous interviewing.

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