Combine two separate SimDesign objects by row
This function combines two Monte Carlo simulations executed by
SimDesign
's runSimulation
function which, for all
intents and purposes, could have been executed in a single run.
This situation arises when a simulation has been completed, however
the Design
object was later modified to include more levels in the
defined simulation factors. Rather than re-executing the previously completed
simulation combinations, only the new combinations need to be evaluated
into a different object and then rbind
together to create the complete
object combinations.
## S3 method for class 'SimDesign' rbind(...)
... |
two or more |
same object that is returned by runSimulation
Phil Chalmers rphilip.chalmers@gmail.com
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
## Not run: # modified example from runSimulation() Design <- createDesign(N = c(10, 20), SD = c(1, 2)) Generate <- function(condition, fixed_objects = NULL) { dat <- with(condition, rnorm(N, 10, sd=SD)) dat } Analyse <- function(condition, dat, fixed_objects = NULL) { ret <- mean(dat) # mean of the sample data vector ret } Summarise <- function(condition, results, fixed_objects = NULL) { ret <- c(mu=mean(results), SE=sd(results)) # mean and SD summary of the sample means ret } Final1 <- runSimulation(design=Design, replications=1000, generate=Generate, analyse=Analyse, summarise=Summarise) Final1 ### # later decide that N = 30 should have also been investigated. Rather than # running the following object .... newDesign <- createDesign(N = c(10, 20, 30), SD = c(1, 2)) # ... only the new subset levels are executed to save time subDesign <- subset(newDesign, N == 30) subDesign Final2 <- runSimulation(design=subDesign, replications=1000, generate=Generate, analyse=Analyse, summarise=Summarise) Final2 # glue results together by row into one object as though the complete 'Design' # object were run all at once Final <- rbind(Final1, Final2) Final summary(Final) ## End(Not run)
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