The importance of type i error rates when studying bias in monte carlo studies in statistics

Michael Harwell

Research output: Contribution to journalArticlepeer-review

Abstract

Two common outcomes of Monte Carlo studies in statistics are bias and Type I error rate. Several versions of bias statistics exist but all employ arbitrary cutoffs for deciding when bias is ignorable or non-ignorable. This article argues Type I error rates should be used when assessing bias.

Original languageEnglish (US)
Article numbereP3295
JournalJournal of Modern Applied Statistical Methods
Volume18
Issue number1
DOIs
StatePublished - 2019

Keywords

  • Bias
  • Monte carlo studies
  • Statistics
  • Type I errors

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