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66 lines
1.5 KiB
R
66 lines
1.5 KiB
R
# Unit Test - gpttools
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test_that("ci_plot produces a valid plot, OLR", {
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data(talos)
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talos[, "mrs_1"] <- factor(talos[, "mrs_1"], ordered = TRUE)
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testthat::expect_true(inherits(ci_plot(
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ds = talos,
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x = "rtreat",
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y = "mrs_1",
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vars = c("hypertension", "diabetes")
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),
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"ggplot"))
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})
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test_that("ci_plot produces a valid plot", {
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data(talos)
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talos[, "mrs_1"] <-
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factor(ifelse(talos[, "mrs_1"] %in% c("0", "1"), 1, 2))
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testthat::expect_true(inherits(ci_plot(
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ds = talos,
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x = "rtreat",
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y = "mrs_1",
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vars = c("hypertension", "diabetes")
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),
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"ggplot"))
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})
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test_that("ci_plot gives error if outcome is not factor", {
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data(talos)
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testthat::expect_error(ci_plot(
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ds = talos,
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x = "rtreat",
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y = "mrs_1",
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vars = c("hypertension", "diabetes")
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))
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})
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test_that("ci_plot produces a valid plot", {
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data(talos)
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talos[, "mrs_1"] <-
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factor(ifelse(talos[, "mrs_1"] %in% c("0", "1"), 1, 2))
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testthat::expect_true(inherits(
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ci_plot(
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ds = talos,
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x = "rtreat",
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y = "mrs_1",
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vars = c("hypertension", "diabetes"),
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lbls = c("Intercept", "Placebo",
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"Hypertension", "Diabetes")
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),
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"ggplot"
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))
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})
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test_that("ci_plot produces a valid plot with method='model'", {
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iris$ord<-factor(sample(1:3,size=nrow(iris),replace=TRUE),ordered=TRUE)
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lm <- MASS::polr(ord~., data=iris, Hess=TRUE, method="logistic")
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expect_true(inherits(
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ci_plot(
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ds = lm,
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method = "model"
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),
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"ggplot"
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))
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})
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