Nothing
data("lalonde", package="cobalt")
psCols <- c("age", "educ", "married", "nodegree")
treatVal <- "treat"
responseVal <- "re78"
pairDistVal <- c("age", "married", "educ", "nodegree")
exactVal <- c("educ")
myBalVal <- c("race")
r1s <- c( 0.1, 0.3, 0.5, 0.7, 0.9,1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7)
r2s <- c(0.01)
res1 <- dist_bal_match(data=lalonde, treat_col= treatVal,
marg_bal_col = myBalVal,
exclusion_penalty=r1s,
balance_penalty=r2s,
dist_col = pairDistVal,
exact_col = exactVal,
propensity_col = psCols,
max_unmatched = 0.1,
caliper_option=NULL,
tol=1e-1, max_iter=0, rho_max_factor = 10)
## 1. Some successful check on function dist_bal_match
test_that("dist_bal_match test with correct input", {
expect_equal(0, sum(unlist(lapply(res1, is.na))))
expect_equal(res1$version, "Basic")
expect_equal(length(res1$matchList), 13)
expect_equal(length(res1$fPair), length(res1$fMarginal))
expect_equal(length(res1$fPair), length(res1$fExclude))
})
## 2. Check that dist_bal_match can handle incorrect input
test_that("dist_bal_match test with wrong input", {
expect_error(dist_bal_match(lalonde, NULL, NULL))
expect_error(dist_bal_match(lalonde, "wrongTreat", "wrongBal"))
})
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