A strategy for using bias and RMSE as outcomes in Monte Carlo Studies in statistics

Michael Harwell

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

To help ensure important patterns of bias and accuracy are detected in Monte Carlo studies in statistics this paper proposes conditioning bias and root mean square error (RMSE) measures on estimated Type I and Type II error rates. A small Monte Carlo study is used to illustrate this argument.

Original languageEnglish (US)
Article numbereP2938
JournalJournal of Modern Applied Statistical Methods
Volume17
Issue number2
DOIs
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 Wayne State University.

Keywords

  • Analysis of outcomes
  • Bias
  • Monte Carlo
  • RMSE

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