# NOT RUN {
loading <- matrix(0, 6, 1)
loading[1:6, 1] <- NA
LY <- bind(loading, 0.7)
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))
summary(Output)
# Get the power of all possible combinations of n and pmMCAR
getPower(Output)
# Get the power of the combinations of n of 100 and 200 and pmMCAR of 0, 0.1, and 0.2
getPower(Output, nVal=c(100, 200), pmMCARval=c(0, 0.1, 0.2))
# }
Run the code above in your browser using DataLab