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.
DOI
10.22237/jmasm/1551907966
Recommended Citation
Harwell, M. (2018). A strategy for using bias and RMSE as outcomes in Monte Carlo studies in statistics. Journal of Modern Applied Statistical Methods, 17(2), eP2938. doi: 10.22237/jmasm/1551907966
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
