## Not run: ------------------------------------
# #########################
# ### real data example ###
# #########################
# # Multiple group path model for facial burns example.
#
# # model syntax with starting values.
# burns.model <- 'Selfesteem ~ Age + c(m1, f1)*TBSA + HADS +
# start(-.10, -.20)*TBSA
# HADS ~ Age + c(m2, f2)*TBSA + RUM +
# start(.10, .20)*TBSA '
#
#
# # constraints syntax
# burns.constraints <- 'f2 > 0 ; m1 < 0
# m2 > 0 ; f1 < 0
# f2 > m2 ; f1 < m1'
#
# # we only generate 2 bootstrap samples in this example; in practice
# # you may wish to use a much higher number.
# # the double bootstrap was switched off; in practice you probably
# # want to set it to "standard".
# example1 <- InformativeTesting(model = burns.model, data = FacialBurns,
# R = 2, constraints = burns.constraints,
# double.bootstrap = "no", group = "Sex")
# example1
# plot(example1)
#
# ##########################
# ### artificial example ###
# ##########################
# # Simple ANOVA model with 3 groups (N = 20 per group)
# set.seed(1234)
# Y <- cbind(c(rnorm(20,0,1), rnorm(20,0.5,1), rnorm(20,1,1)))
# grp <- c(rep("1", 20), rep("2", 20), rep("3", 20))
# Data <- data.frame(Y, grp)
#
# #create model matrix
# fit.lm <- lm(Y ~ grp, data = Data)
# mfit <- fit.lm$model
# mm <- model.matrix(mfit)
#
# Y <- model.response(mfit)
# X <- data.frame(mm[,2:3])
# names(X) <- c("d1", "d2")
# Data.new <- data.frame(Y, X)
#
# # model
# model <- 'Y ~ 1 + a1*d1 + a2*d2'
#
# # fit without constraints
# fit <- sem(model, data = Data.new)
#
# # constraints syntax: mu1 < mu2 < mu3
# constraints <- ' a1 > 0
# a1 < a2 '
#
# # we only generate 10 bootstrap samples in this example; in practice
# # you may wish to use a much higher number, say > 1000. The double
# # bootstrap is not necessary in case of an univariate ANOVA model.
# example2 <- InformativeTesting(model = model, data = Data.new,
# start = parTable(fit),
# R = 10L, double.bootstrap = "no",
# constraints = constraints)
# example2
# # plot(example2)
## ---------------------------------------------
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