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Sample Size and Model Prediction Accuracy in EQ-5D-5L Valuations Studies: Expected Out-of-Sample Accuracy Based on Resampling with Different Sample Sizes and Alternative Model Specifications.

Tonya Moen HansenKnut StavemKim Rand
Published in: MDM policy & practice (2022)
Increases in sample size beyond a minimum in the range of 300 to 500 respondents provide smaller gains in expected prediction accuracy than alternative modeling approaches.Constrained, nonlinear models; time tradeoff + discrete choice experiment hybrid modeling; and including a random intercept all improved the prediction accuracy of models estimating values for the EQ-5D-5L based on data from 3 different valuation studies.The tested modeling choices can compensate for smaller sample sizes.
Keyphrases
  • machine learning
  • electronic health record
  • big data
  • deep learning
  • decision making