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Session 34. Handling Missing Data in Complex Surveys

Session 34. Handling Missing Data in Complex Surveys.

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Session 34. Handling Missing Data in Complex Surveys

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  1. Session 34. Handling Missing Data in Complex Surveys • Presenters in this session will discuss why it is important not to ignore missing data but to be concerned about it, the pros and cons of imputation, and general methods for handling missing data. In addition, applications of imputation and multiple imputation involving selected NCHS surveys will be discussed. NCHS/DUC , Washington, D.C., August 17, 2010 Presenters: • Trivellore E. Raghunathan, ISR, University of MI • Nathaniel Schenker, ORM, NCHS • Taylor Lewis, ORM, NCHS 1

  2. Missing Data in Surveys • Sample noncontact • Nonparticipation • Partial participation • Refusal • Don’t know • Item nonresponse • Data recording or measurement error • Data processing error • A zero value How do you handle missing data in data analyses? 2

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