SimDesign (version 2.2)

SimResults: Function to read in saved simulation results

Description

If runSimulation was passed the flag save_results = TRUE then the row results corresponding to the design object will be stored to a suitable sub-directory as individual .rds files. While users could use readRDS directly to read these files in themselves, this convenience function will read the desired rows in automatically given the returned object from the simulation. Can be used to read in 1 or more .rds files at once (if more than 1 file is read in then the result will be stored in a list).

Usage

SimResults(results, which, wd = getwd())

Arguments

results

object returned from runSimulation where save_results = TRUE was used

which

a numeric vector indicating which rows should be read in. If missing, all rows will be read in

wd

working directory; default is found with getwd.

Value

the returned result is either a nested list (when length(which) > 1) or a single list (when length(which) == 1) containing the simulation results. Each read-in result refers to a list of 4 elements:

condition

the associate row (ID) and conditions from the respective design object

results

the object with returned from the analyse function, potentially simplified into a matrix or data.frame

errors

a table containing the message and number of errors that caused the generate-analyse steps to be rerun. These should be inspected carefully as they could indicate validity issues with the simulation that should be noted

warnings

a table containing the message and number of non-fatal warnings which arose from the analyse step. These should be inspected carefully as they could indicate validity issues with the simulation that should be noted

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. 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. 10.1080/10691898.2016.1246953

Examples

# NOT RUN {
# }
# NOT RUN {
results <- runSimulation(..., save_results = TRUE)

# row 1 results
row1 <- SimResults(results, 1)

# rows 1:5, stored in a named list
rows_1to5 <- SimResults(results, 1:5)

# all results
rows_all <- SimResults(results)

# }