mdes.bcra3r2
calculates minimum detectable effect size (MDES) for designs with 3-levels
where level 2 units are randomly assigned to treatment and control groups within level 3 units (random blocks).
mdes.bcra3r2(power=.80, alpha=.05, two.tail=TRUE, rho2, rho3, omega3, P=.50, g3=0, R12=0, R22=0, RT32=0, n, J, K, ...)
TRUE
for two-tailed hypothesis testing, FALSE
for one-tailed hypothesis testing. MDES formula and further definition of design parameters can be found in Dong & Maynard (2013).
Dong & Maynard (2013). PowerUp!: A Tool for Calculating Minum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies,Journal of Research on Educational Effectiveness, 6(1), 24-6.
power.bcra3r2, mrss.bcra3r2, optimal.bcra3r2
## Not run:
#
# mdes.bcra3r2(rho3=.13, rho2=.10, omega3=.40,
# n=10, J=6, K=24)
#
# ## End(Not run)
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