Monday Research Seminar Series
February 4, Jerry Reiter
Noon, Hamburg Hall, Room 1502
The Multiple Adaptations of Multiple Imputation
Multiple imputation was first conceived as a tool that statistical agencies could use to handle nonresponse in large sample, public use surveys. In the last two decades, the multiple imputation framework has been adapted for other statistical contexts. As examples, individual researchers use multiple imputation to handle missing data in small samples; statistical agencies disseminate multiply-imputed datasets for purposes of protecting data confidentiality; and, survey methodologists use multiple imputation to correct for measurement errors. In this talk, I describe some of the adaptations of the multiple imputation framework, with particular attention to multiple imputation for missing data and for protecting data confidentiality.
