Nothing
nf_grips <- suppressMessages(suppressWarnings(N_FACTORS(GRiPS_raw)))
test_that("output class and dimensions are correct", {
expect_is(nf_grips, "N_FACTORS")
expect_is(nf_grips$outputs, "list")
expect_is(nf_grips$settings, "list")
expect_is(nf_grips$n_factors, "numeric")
expect_named(nf_grips, c("outputs", "n_factors", "settings"))
expect_named(nf_grips$outputs, c("bart_out", "kmo_out", "cd_out", "ekc_out",
"hull_out", "kgc_out", "parallel_out",
"scree_out", "smt_out"))
expect_named(nf_grips$n_factors, c("nfac_CD", "nfac_EKC", "nfac_HULL_CAF",
"nfac_HULL_CFI", "nfac_HULL_RMSEA",
"nfac_KGC_PCA", "nfac_KGC_SMC",
"nfac_KGC_EFA",
"nfac_PA_PCA", "nfac_PA_SMC", "nfac_PA_EFA",
"nfac_SMT_chi", "nfac_RMSEA", "nfac_AIC"))
expect_named(nf_grips$settings, c("criteria", "suitability", "N", "use",
"n_factors_max", "N_pop", "N_samples", "alpha",
"cor_method", "max_iter_CD", "n_fac_theor",
"method", "gof", "eigen_type_HULL",
"eigen_type_other", "n_factors", "n_datasets",
"percent", "decision_rule"))
})
x <- rnorm(100)
y <- rnorm(100)
z <- x + y
burt <- matrix(c(1.00, 0.83, 0.81, 0.80, 0.71, 0.70, 0.54, 0.53, 0.59, 0.24, 0.13,
0.83, 1.00, 0.87, 0.62, 0.59, 0.44, 0.58, 0.44, 0.23, 0.45, 0.21,
0.81, 0.87, 1.00, 0.63, 0.37, 0.31, 0.30, 0.12, 0.33, 0.33, 0.36,
0.80, 0.62, 0.63, 1.00, 0.49, 0.54, 0.30, 0.28, 0.42, 0.29, -0.06,
0.71, 0.59, 0.37, 0.49, 1.00, 0.54, 0.34, 0.55, 0.40, 0.19, -0.10,
0.70, 0.44, 0.31, 0.54, 0.54, 1.00, 0.50, 0.51, 0.31, 0.11, 0.10,
0.54, 0.58, 0.30, 0.30, 0.34, 0.50, 1.00, 0.38, 0.29, 0.21, 0.08,
0.53, 0.44, 0.12, 0.28, 0.55, 0.51, 0.38, 1.00, 0.53, 0.10, -0.16,
0.59, 0.23, 0.33, 0.42, 0.40, 0.31, 0.29, 0.53, 1.00, -0.09, -0.10,
0.24, 0.45, 0.33, 0.29, 0.19, 0.11, 0.21, 0.10, -0.09, 1.00, 0.41,
0.13, 0.21, 0.36, -0.06, -0.10, 0.10, 0.08, -0.16, -0.10, 0.41, 1.00),
nrow = 11, ncol = 11)
test_that("errors etc. are thrown correctly", {
expect_error(N_FACTORS(1:10), " 'x' is neither a matrix nor a dataframe. Either provide a correlation matrix or a dataframe or matrix with raw data.\n")
expect_warning(N_FACTORS(GRiPS_raw, N = 10), " 'N' was set and data entered. Taking N from data.\n")
expect_error(N_FACTORS(cbind(x, y, z, z + 1, y + 1, x + 1)), " Correlation matrix is singular, no further analyses are performed\n")
expect_warning(N_FACTORS(test_models$baseline$cormat, N = 500), " 'x' was a correlation matrix but CD needs raw data. Skipping CD.\n")
expect_warning(N_FACTORS(burt, N = 170, criteria = c("PARALLEL", "EKC")), "Matrix was not positive definite, smoothing was done")
})
rm(nf_grips, x, y, z, burt)
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