Description Usage Arguments Author(s) References Examples
Given the results from a simulation with runSimulation
form an ANOVA table (without
pvalues) with effect sizes based on the etasquared statistic. These results provide approximate
indications of observable simulation effects, therefore these ANOVAbased results are generally useful
as exploratory rather than inferential tools.
1 
formula 
an R formula generally of a form suitable for 
dat 
an object returned from 
subset 
an optional argument to be passed to 
rates 
logical; does the dependent variable consist of rates (e.g., returned from

Phil Chalmers [email protected]
Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte
Carlo simulation. Journal of Statistics Education, 24
(3), 136156.
http://www.tandfonline.com/doi/full/10.1080/10691898.2016.1246953
1 2 3 4 5 6 7 8 9 10  data(BF_sim)
# all results (not usually good to mix Power and Type I results together)
SimAnova(alpha.05.F ~ (groups_equal + distribution)^2, BF_sim)
# only use anova for Type I error conditions
SimAnova(alpha.05.F ~ (groups_equal + distribution)^2, BF_sim, subset = var_ratio == 1)
# run all DVs at once using the same formula
SimAnova(~ groups_equal * distribution, BF_sim, subset = var_ratio == 1)

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