MMRM versus MI in Dealing with Missing Data—A Comparison Based on 25 NDA Data Sets

Both multiple imputation and mixed-effects model repeated measures approaches appear to be better choices than the traditional last-observation-carried-forward approach in analyzing incomplete clinical trial data sets in drug development research

Ohidul Siddiqui

2011

Scholarcy highlights

  • Both multiple imputation and mixed-effects model repeated measures approaches appear to be better choices than the traditional last-observation-carried-forward approach in analyzing incomplete clinical trial data sets in drug development research
  • relative performances of these two approaches are unknown in controlling type I error rate
  • Little research has been done in comparing robustness of the two approaches
  • The MMRM approach appears to be a better choice in maintaining statistical properties of a test

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