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Compute the relative absolute bias of multiple estimators

Source: R/summary_functions.R
RAB.Rd

Computes the relative absolute bias given the bias estimates for multiple estimators.

Usage

RAB(x, percent = FALSE, unname = FALSE)

Arguments

x

a numeric vector of bias estimates (see bias), where the first element will be used as the reference

percent

logical; change returned result to percentage by multiplying by 100? Default is FALSE

unname

logical; apply unname to the results to remove any variable names?

Value

returns a vector of absolute bias ratios indicating the relative bias effects compared to the first estimator. Values less than 1 indicate better bias estimates than the first estimator, while values greater than 1 indicate worse bias than the first estimator

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. doi:10.20982/tqmp.16.4.p248

Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte Carlo simulation. Journal of Statistics Education, 24(3), 136-156. doi:10.1080/10691898.2016.1246953

Author

Phil Chalmers rphilip.chalmers@gmail.com

Examples


pop <- 1
samp1 <- rnorm(5000, 1)
bias1 <- bias(samp1, pop)
samp2 <- rnorm(5000, 1)
bias2 <- bias(samp2, pop)

RAB(c(bias1, bias2))
#> [1]  1.00000 31.51306
RAB(c(bias1, bias2), percent = TRUE) # as a percentage
#> [1]  100.000 3151.306