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Identifying Attrition Phases in Survey Data: Applicability and Assessment Study.

Camille J HochheimerRoy T SaboRobert A PereraNitai D MukhopadhyayAlex H Krist
Published in: Journal of medical Internet research (2019)
The user-specified method set to a low threshold correctly identified the attrition phases. Hypothesis testing methods, although sensitive at times, were unable to accurately identify the attrition phases. These results strengthen the case for further development of and research surrounding the science of attrition.
Keyphrases
  • public health
  • electronic health record
  • cross sectional
  • machine learning