Summarise: Summarise simulated data using various population comparison...

In SimDesign: Structure for Organizing Monte Carlo Simulation Designs

Summarise simulated data using various population comparison statistics

Description

This collapses the simulation results within each condition to composite estimates such as RMSE, bias, Type I error rates, coverage rates, etc. See the See Also section below for useful functions to be used within Summarise.

Usage

Summarise(condition, results, fixed_objects)

Arguments

condition	a single row from the design input from runSimulation (as a data.frame), indicating the simulation conditions
results	a tibble data frame (if Analyse returned a named numeric vector of any length) or a list (if Analyse returned a list or multi-rowed data.frame) containing the analysis results from Analyse, where each cell is stored in a unique row/list element
fixed_objects	object passed down from runSimulation

Value

for best results should return a named numeric vector or data.frame with the desired meta-simulation results. Named list objects can also be returned, however the subsequent results must be extracted via SimExtract

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. \Sexpr[results=rd]{tools:::Rd_expr_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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10691898.2016.1246953")}

See Also

bias, RMSE, RE, EDR, ECR, MAE, SimExtract

Examples

## Not run: 

summarise <- function(condition, results, fixed_objects) {

    #find results of interest here (alpha < .1, .05, .01)
    lessthan.05 <- EDR(results, alpha = .05)

    # return the results that will be appended to the design input
    ret <- c(lessthan.05=lessthan.05)
    ret
}


## End(Not run)

SimDesign documentation built on April 3, 2025, 6:06 p.m.