View source: R/rbind.SimDesign.R
rbind.SimDesign | R Documentation |
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.
\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")}
## Not run:
# modified example from runSimulation()
Design <- createDesign(N = c(10, 20),
SD = c(1, 2))
Generate <- function(condition, fixed_objects) {
dat <- with(condition, rnorm(N, 10, sd=SD))
dat
}
Analyse <- function(condition, dat, fixed_objects) {
ret <- mean(dat) # mean of the sample data vector
ret
}
Summarise <- function(condition, results, fixed_objects) {
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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