#Tests for specific github issues
skip_on_cran()
test_that("(#71) `addl` argument not throwing correct error when variable not available", {
#Note: actual error was something else, but addl should have thrown a more informative error
skip_if_not_installed("MatchIt")
data("lalonde")
m <- MatchIt::matchit(treat ~ age + educ, data = lalonde, distance = "scaled_euclidean")
expect_error(bal.tab(m, addl = "race"),
"The variable \"race\" cannot be found. Be sure it is entered correctly or supply a dataset that contains this varialble to `data`.",
fixed = TRUE)
expect_no_condition(bal.tab(m, addl = "race", data = lalonde))
})
test_that("(#74) bal.tab() works with mnps objects", {
skip_if_not_installed("twang")
data("lalonde")
mnps <- twang::mnps(race ~ age + educ + married + re74,
data = lalonde,
estimand = "ATT",
treatATT = "white",
verbose = FALSE,
stop.method = c("es.mean"),
n.trees = 1000)
expect_no_condition(
bal.tab(mnps, un = TRUE, disp = c("m", "sd"))
)
})
test_that("(#76) bal.tab() doesn't produce an error with missing covariates", {
data("lalonde_mis")
expect_warning(
b <- bal.tab(treat ~ age + educ + race + married + nodegree + re74 + re75,
data = lalonde_mis, s.d.denom = "pooled"),
"Missing values exist in the covariates. Displayed values omit these observations.",
fixed = TRUE
)
expect_no_error(
suppressWarnings(
b <- bal.tab(treat ~ age + educ + race + married + nodegree + re74 + re75,
data = lalonde_mis, s.d.denom = "pooled")
)
)
expect_identical(rownames(b$Balance),
c("age", "educ", "race_black", "race_hispan", "race_white",
"married", "married:<NA>", "nodegree",
"re74", "re74:<NA>", "re75", "re75:<NA>"))
})
test_that("(#77) no conflict with `cluster` argument to bal.tab() when {caret} is loaded", {
skip_if_not_installed("caret")
library(caret)
data("lalonde")
expect_no_condition(bal.tab(treat ~ age + educ + race, data = lalonde, cluster = "married",
s.d.denom = "pooled"))
})
test_that("(#82) love.plot() doesn't throw any ggplo2-related warnings with multiple stats", {
skip_if_not_installed("MatchIt")
data("lalonde")
m.out <- MatchIt::matchit(treat ~ age + educ + race + married +
nodegree + re74 + re75,
data = lalonde)
expect_no_condition(love.plot(m.out, stats = c("mean.diffs", "variance.ratios"),
binary = "std"))
})
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