# NOT RUN {
# Specify Sample Size by n
loading <- matrix(0, 6, 1)
loading[1:6, 1] <- NA
LY <- bind(loading, 0.4)
RPS <- binds(diag(1))
RTE <- binds(diag(6))
CFA.Model <- model(LY = LY, RPS = RPS, RTE = RTE, modelType="CFA")
# Specify both sample size and percent missing completely at random. Note that more fine-grained
# values of n and pmMCAR is needed, e.g., n=seq(50, 500, 1) and pmMCAR=seq(0, 0.2, 0.01)
Output <- sim(NULL, model=CFA.Model, n=seq(100, 200, 20), pmMCAR=c(0, 0.1, 0.2))
# Find the power of all possible combination of N and pmMCAR
cover <- getCoverage(Output, coverValue = 0)
# Find the sample size that provides the power of 0.8
findCoverage(cover, "N", 0.20)
# }
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