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Missing Data pp 253-275 | Cite as

Using Modern Missing Data Methods with Auxiliary Variables to Mitigate the Effects of Attrition on Statistical Power

  • John W. Graham
  • Linda M. Collins
Chapter
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Abstract

Missing data in a field experiment may arise from a number of sources. Participants may skip over questions inadvertently or refuse to answer them; they may offer an illegible response; they may fail to complete a questionnaire; or they may be absent from an entire measurement session in a longitudinal study. The last is often called wave nonresponse. Many participants who are unavailable for one or more occasions of measurement are available at later occasions. We define attrition is a special case of wave nonresponse in which a participant drops out of a study after a certain time and is no longer available at any subsequent wave of data collection.

Keywords

Auxiliary Variable Full Information Maximum Likelihood Artificial Data Main Dependent Variable Intervention Scientist 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • John W. Graham
    • 1
  • Linda M. Collins
  1. 1.Department of Biobehavioral HealthThe Pennsylvania State UniversityUniversity ParkUSA

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