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Modeling insufficient effort responses in mixed-worded scales.

Kuan-Yu JinMing Ming Chiu
Published in: Behavior research methods (2023)
Surveys often add reverse-coded questions to monitor respondents with insufficient effort responses (IERs) but often wrongly assume that all respondents consistently answer all questions with full effort. By contrast, this study expanded the mixture model for IERs and ran a simulation via LatentGOLD to show the harmful consequences of ignoring IERs to positively and negatively worded questions: less test reliability, bias and less accuracy in slope and intercept parameters. We showed its practical application to two public data sets: Machiavellianism (five-point scale) and self-reported depression (four-point scale).
Keyphrases
  • healthcare
  • depressive symptoms
  • electronic health record
  • big data
  • cross sectional
  • sleep quality
  • computed tomography
  • artificial intelligence