swh:1:snp:2c68a6c5a8af2f06ac2c0225927f25b54fd1f9d0
Tip revision: 6313ce21ea98857cf95d996de7978cfd52175e59 authored by Dominique Makowski on 08 April 2021, 04:40:02 UTC
version 0.9.0
version 0.9.0
Tip revision: 6313ce2
test-blavaan.R
if (suppressPackageStartupMessages(require("bayestestR", quietly = TRUE)) && require("testthat")) {
test_that("blavaan, all", {
skip_if_not_installed("blavaan")
skip_if_not_installed("lavaan")
require(blavaan)
data("PoliticalDemocracy", package = "lavaan")
model <- '
# latent variable definitions
dem60 =~ y1 + a*y2
dem65 =~ y5 + a*y6
# regressions
dem65 ~ dem60
# residual correlations
y1 ~~ y5
'
model2 <- '
# latent variable definitions
dem60 =~ y1 + a*y2
dem65 =~ y5 + a*y6
# regressions
dem65 ~ 0*dem60
# residual correlations
y1 ~~ 0*y5
'
suppressWarnings(capture.output({
bfit <- blavaan::bsem(model, data = PoliticalDemocracy,
n.chains = 1, burnin = 50, sample = 100)
bfit2 <- blavaan::bsem(model2, data = PoliticalDemocracy,
n.chains = 1, burnin = 50, sample = 100)
}))
x <- point_estimate(bfit, centrality = "all", dispersion = TRUE)
expect_true(all(c("Median", "MAD", "Mean", "SD", "MAP", "Component") %in% colnames(x)))
expect_equal(nrow(x), 14)
x <- eti(bfit)
expect_equal(nrow(x), 14)
x <- hdi(bfit)
expect_equal(nrow(x), 14)
x <- p_direction(bfit)
expect_equal(nrow(x), 14)
x <- rope(bfit)
expect_equal(nrow(x), 14)
x <- p_rope(bfit)
expect_equal(nrow(x), 14)
x <- p_map(bfit)
expect_equal(nrow(x), 14)
x <- p_significance(bfit)
expect_equal(nrow(x), 14)
x <- equivalence_test(bfit)
expect_equal(nrow(x), 14)
x <- estimate_density(bfit)
expect_equal(length(unique(x$Parameter)), 14)
## Bayes factors ----
x <- expect_warning(bayesfactor_models(bfit, bfit2))
expect_true(x$BF[2] < 1)
bfit_prior <- unupdate(bfit)
capture.output(x <- bayesfactor_parameters(bfit, prior = bfit_prior))
expect_equal(nrow(x), 14)
x <- expect_warning(si(bfit, prior = bfit_prior))
expect_equal(nrow(x), 14)
x <- expect_warning(weighted_posteriors(bfit, bfit2))
expect_equal(ncol(x), 14)
## Prior/posterior checks ----
suppressWarnings(x <- check_prior(bfit))
expect_equal(nrow(x), 13)
x <- check_prior(bfit, simulate_priors = FALSE)
expect_equal(nrow(x), 14)
x <- diagnostic_posterior(bfit)
expect_equal(nrow(x), 14)
x <- simulate_prior(bfit)
expect_equal(ncol(x), 13)
# YES this is 13! We have two parameters with the same prior.
x <- describe_prior(bfit)
expect_equal(nrow(x), 13)
# YES this is 13! We have two parameters with the same prior.
x <- describe_posterior(bfit, test = "all")
expect_equal(nrow(x), 14)
})
}