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

Research output: Contribution to journalArticle

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 - Jan 1 2018

Fingerprint

Monte Carlo Study
Mean square error
Roots
Statistics
Type II error
Conditioning
Error Rate
Strategy
Monte Carlo study
Type I and type II errors

Keywords

  • Analysis of outcomes
  • Bias
  • Monte Carlo
  • RMSE

Cite this

A strategy for using bias and RMSE as outcomes in Monte Carlo Studies in statistics. / Harwell, Michael R.

In: Journal of Modern Applied Statistical Methods, Vol. 17, No. 2, eP2938, 01.01.2018.

Research output: Contribution to journalArticle

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