mdes.bcra4f3
calculates minimum detectable effect size (MDES) for designs with 4-levels
where level 3 units are randomly assigned to treatment and control groups within level 4 units (fixed blocks).
mdes.bcra4f3(power=.80, alpha=.05, two.tail=TRUE, rho2, rho3, P=.50, R12=0, R22=0, R32=0, g3=0, n, J, K, L, ...)
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.bcra4f3, mrss.bcra4f3, optimal.bcra4f3
## Not run:
#
# mdes.bcra4f3(rho3=.15, rho2=.15,
# n=10, J=4, K=4, L=15)
# ## End(Not run)
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