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Activity Number: 454
Type: Invited
Date/Time: Wednesday, August 9, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Education
Abstract - #304992
Title: An Introduction to Incomplete Data Regression Methods Used in Practice
Author(s): Nicholas J. Horton*+ and Ken P. Kleinman
Companies: Smith College and Harvard Medical School
Address: Clark Science Center, Northampton, MA, 01063-0001,
Keywords: multiple imputation ; incomplete data ; missing data ; missing at random ; nonignorable nonresponse ; maximum likelihood
Abstract:

Missing data arise in almost all real-world studies, and an extensive statistical literature has developed to address these complications. Software to account for missing values is now widely available and increasingly used in published studies. In this talk, we will review these methods, describe software implementations, and summarize the advantages and limitations of their use in practice.

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