AnalyseIf | R Documentation |
Analyse()
function should be executedThis function is designed to prevent specific analysis function executions when the
design conditions are not met. Primarily useful when the analyse
argument to
runSimulation
was input as a named list object, however some of the
analysis functions are not interesting/compatible with the generated data and should
therefore be skipped.
AnalyseIf(x, condition = NULL)
x |
logical statement to evaluate. If the statement evaluates to |
condition |
(optional) the current design condition. This does not need to be supplied
if the expression in |
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")}
Analyse
, runSimulation
## Not run:
Design <- createDesign(N=c(10,20,30), var.equal = c(TRUE, FALSE))
Generate <- function(condition, fixed_objects) {
Attach(condition)
dat <- data.frame(DV = rnorm(N*2), IV = gl(2, N, labels=c('G1', 'G2')))
dat
}
# always run this analysis for each row in Design
Analyse1 <- function(condition, dat, fixed_objects) {
mod <- t.test(DV ~ IV, data=dat)
mod$p.value
}
# Only perform analysis when variances are equal and N = 20 or 30
Analyse2 <- function(condition, dat, fixed_objects) {
AnalyseIf(var.equal && N %in% c(20, 30), condition)
mod <- t.test(DV ~ IV, data=dat, var.equal=TRUE)
mod$p.value
}
Summarise <- function(condition, results, fixed_objects) {
ret <- EDR(results, alpha=.05)
ret
}
#-------------------------------------------------------------------
# append names 'Welch' and 'independent' to associated output
res <- runSimulation(design=Design, replications=100, generate=Generate,
analyse=list(Welch=Analyse1, independent=Analyse2),
summarise=Summarise)
res
# leave results unnamed
res <- runSimulation(design=Design, replications=100, generate=Generate,
analyse=list(Analyse1, Analyse2),
summarise=Summarise)
## End(Not run)
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