Nothing
library("testthat")
# simulated data to test
set.seed(1000)
n <- 1000
cov <- data.frame(
ftime = rexp(n),
fstatus = sample(0:2, n, replace = TRUE),
x1 = runif(n),
x2 = runif(n),
x3 = runif(n)
)
library(rms)
dd <<- datadist(cov)
options(datadist = "dd")
test_that("Simple linear regression", {
fit <- mtcars |>
set_column_labels(cyl = "Number of cylinders",
hp = "Gross horsepower") |>
(\(x) lm(mpg ~ cyl + disp + hp, data = x))()
expect_s3_class(forestplotRegrObj(regr.obj = fit),
"gforge_forestplot")
})
test_that("Simple linear regression", {
fit <- mtcars |>
set_column_labels(cyl = "Number of cylinders",
hp = "Gross horsepower") |>
(\(x) glm(mpg ~ cyl + disp + hp, data = x, family = gaussian()))()
expect_s3_class(forestplotRegrObj(regr.obj = fit),
"gforge_forestplot")
})
test_that("Simple linear regression", {
data <- mtcars |>
set_column_labels(cyl = "Number of cylinders",
hp = "Gross horsepower")
fit1 <- lm(mpg ~ cyl + disp + hp, data = data)
fit2 <- lm(mpg ~ cyl + disp + gear, data = data)
expect_s3_class(forestplotRegrObj(regr.obj = list(fit1, fit2)),
"gforge_forestplot")
})
test_that("Basic test for coverage for forestplotRegrObj", {
fit1 <- cph(Surv(ftime, fstatus == 1) ~ x1 + x2 + x3, data = cov)
fit2 <- cph(Surv(ftime, fstatus == 2) ~ x1 + x2 + x3, data = cov)
ret <- forestplotRegrObj(
regr.obj = list(fit1, fit2),
col = fpColors(box = c("darkblue", "darkred")),
postprocess_estimates.fn = \(x) filter(x, str_detect(column_term, "(x2|x3)")),
legend = c("First model", "Second model"),
legend_args = fpLegend(title = "Models"))
expect_equal(ret$is.summary, rep(c(TRUE, FALSE, FALSE), 2))
})
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