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# Holzinger data
library(lavaan)
HS.full <- HolzingerSwineford1939
HS.df <- HolzingerSwineford1939[,c("x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9")]
HS.model <- 'visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9'
# test case when data contains non-numeric columns
expect_error(REM_CFA(X = HS.full, model = HS.model))
# test case when dimension of model does not match dimension of data
expect_error(REM_CFA(X = HS.df[,-1], model = HS.model))
# test case when delta < 0
expect_error(REM_CFA(X = HS.df, delta = -0.05, model = HS.model))
# test case when delta > 1
expect_error(REM_CFA(X = HS.df, delta = 1.05, model = HS.model))
# test case with unexpected model form
HS.model2 <- 'visual =~ x1 + 2 x2 + x3
speed =~ x7 + x8 + x9
textual =~ x4 + x5+ x6'
expect_error(REM_CFA(X = HS.df, model = HS.model2))
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