Nothing
# default
test_that('extract trilogit by means of the default method', {
list(
B = matrix(rnorm(8), 4, 2, dimnames = list(paste0('X', 0:3))),
levels = LETTERS[1:3]
) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'list')
})
# ordinal::clm
test_that('extract trilogit from "ordinal::clm"', {
cross_1year %>%
mutate(finalgrade = factor(
x = finalgrade,
levels = c('Low', 'Average', 'High'),
ordered = TRUE)
) %>%
MASS::polr(finalgrade ~ gender + irregularity, data = .) %>%
extract3logit -> modref
cross_1year %>%
mutate(finalgrade = factor(
x = finalgrade,
levels = c('Low', 'Average', 'High'),
ordered = TRUE)
) %>%
ordinal::clm(finalgrade ~ gender + irregularity, data = .) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'ordinal::clm')
expect_identical(model$levels[model$ool], modref$levels)
expect_equal(model$B, modref$B, tolerance = 1e-6)
expect_equal(model$alpha, modref$alpha, tolerance = 1e-6)
})
# ordinal::clm2
test_that('extract trilogit from "ordinal::clm2"', {
cross_1year %>%
mutate(finalgrade = factor(
x = finalgrade,
levels = c('Low', 'Average', 'High'),
ordered = TRUE)
) %>%
MASS::polr(finalgrade ~ gender + irregularity, data = .) %>%
extract3logit -> modref
cross_1year %>%
mutate(finalgrade = factor(
x = finalgrade,
levels = c('Low', 'Average', 'High'),
ordered = TRUE)
) %>%
ordinal::clm2(finalgrade ~ gender + irregularity, data = .) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'ordinal::clm2')
expect_identical(model$levels[model$ool], modref$levels)
expect_equal(model$B, modref$B, tolerance = 1e-6)
expect_equal(model$alpha, modref$alpha, tolerance = 1e-6)
})
# mlogit::mlogit
test_that('extract trilogit from "mlogit::mlogit"', {
cross_1year %>%
nnet::multinom(
formula = employment_sit ~ gender + finalgrade,
data = .,
trace = FALSE
) %>%
extract3logit -> modref
cross_1year %>%
mlogit::mlogit.data(choice = 'employment_sit', shape = 'wide') %>%
mlogit::mlogit(employment_sit ~ 0 | gender + finalgrade, data = .) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'mlogit::mlogit')
#expect_identical(model$levels[model$ool], modref$levels)
#expect_equal(model$B[ , 2:1], modref$B, tolerance = 1e-4)
#expect_equal(model$vcovB, modref$vcovB)
})
# nnet::multinom
test_that('extract trilogit from "nnet::multinom"', {
cross_1year %>%
nnet::multinom(
formula = employment_sit ~ gender + finalgrade,
data = .,
trace = FALSE
) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'nnet::multinom')
})
# MASS::polr
test_that('extract trilogit from "MASS::polr"', {
cross_1year %>%
mutate(finalgrade = factor(
x = finalgrade,
levels = c('Low', 'Average', 'High'),
ordered = TRUE)
) %>%
MASS::polr(finalgrade ~ gender + irregularity, data = .) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'MASS::polr')
})
# VGAM::vgam
test_that('extract trilogit from "VGAM::vgam"', {
cross_1year %>%
nnet::multinom(
formula = employment_sit ~ gender + finalgrade,
data = .,
trace = FALSE
) %>%
extract3logit -> modref
cross_1year %>%
VGAM::vgam(
formula = employment_sit ~ gender + finalgrade,
family = VGAM::multinomial(),
data = .
) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'VGAM::vgam')
expect_identical(model[['ool']], c(2L, 3L, 1L))
expect_identical(model$levels[model$ool], modref$levels)
#expect_equal(model$B, modref$B)
#expect_equal(model$vcovB, modref$vcovB)
})
# VGAM::vglm
test_that('extract trilogit from "VGAM::vglm"', {
cross_1year %>%
nnet::multinom(
formula = employment_sit ~ gender + finalgrade,
data = .,
trace = FALSE
) %>%
extract3logit -> modref
cross_1year %>%
VGAM::vglm(
formula = employment_sit ~ gender + finalgrade,
family = VGAM::multinomial(),
data = .
) %>%
extract3logit -> model
expect_is(model, 'model3logit')
expect_identical(model[['readfrom']], 'VGAM::vglm')
expect_identical(model[['ool']], c(2L, 3L, 1L))
expect_identical(model$levels[model$ool], modref$levels)
#expect_equal(model$B, modref$B)
#expect_equal(model$vcovB, modref$vcovB)
})
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