Nothing
settings <- expand.grid(lp = c("dual", "primal"),
purpose = c("find", "test"),
stringsAsFactors = FALSE)
if (requireNamespace("AER", quietly = TRUE)) {
data("MurderRates", package = "AER")
murder_formula <- I(executions > 0) ~ time + income + noncauc + lfp + southern
murder_sep <- as.list(numeric(4))
for (j in seq.int(nrow(settings))) {
murder_sep[[j]] <- glm(murder_formula, data = MurderRates,
family = binomial(),
method = "detect_separation",
implementation = "lpSolveAPI",
linear_program = settings[j, "lp"],
purpose = settings[j, "purpose"])
}
names(murder_sep) <- apply(settings, 1, paste, collapse = "-")
## test that lpSolveAPI implementation returns the same result across linear_program and purpose settings [MurderRates]"
expect_equal(coef(murder_sep[["dual-find"]]), coef(murder_sep[["primal-find"]]))
expect_equal(murder_sep[["dual-find"]]$separation, murder_sep[["primal-find"]]$separation)
expect_equal(murder_sep[["dual-find"]]$separation, murder_sep[["primal-test"]]$separation)
expect_equal(murder_sep[["dual-find"]]$separation, murder_sep[["dual-test"]]$separation)
}
data("endometrial", package = "detectseparation")
endo_sep <- as.list(numeric(4))
for (j in seq.int(nrow(settings))) {
endo_sep[[j]] <- glm(HG ~ I(-NV) + PI + EH,
data = endometrial,
family = binomial("cloglog"),
method = "detect_separation",
implementation = "lpSolveAPI",
linear_program = settings[j, "lp"],
purpose = settings[j, "purpose"])
}
names(endo_sep) <- apply(settings, 1, paste, collapse = "-")
## test that lpSolveAPI implementation returns the same result across linear_program and purpose settings [endometrial]
expect_equal(coef(endo_sep[["dual-find"]]), coef(endo_sep[["primal-find"]]))
expect_equal(endo_sep[["dual-find"]]$separation, endo_sep[["primal-find"]]$separation)
expect_equal(endo_sep[["dual-find"]]$separation, endo_sep[["primal-test"]]$separation)
expect_equal(endo_sep[["dual-find"]]$separation, endo_sep[["dual-test"]]$separation)
data("lizards", package = "detectseparation")
lizo_sep <- as.list(numeric(4))
for (j in seq.int(nrow(settings))) {
lizo_sep[[j]] <- glm(cbind(grahami, opalinus) ~ height + diameter +
light + time,
data = lizards,
family = binomial("logit"),
method = "detect_separation",
implementation = "lpSolveAPI",
linear_program = settings[j, "lp"],
purpose = settings[j, "purpose"])
}
names(lizo_sep) <- apply(settings, 1, paste, collapse = "-")
## test that lpSolveAPI implementation returns the same result across linear_program and purpose settings [lizards]
expect_equal(coef(lizo_sep[["dual-find"]]), coef(lizo_sep[["primal-find"]]))
expect_equal(lizo_sep[["dual-find"]]$separation, lizo_sep[["primal-find"]]$separation)
expect_equal(lizo_sep[["dual-find"]]$separation, lizo_sep[["primal-test"]]$separation)
expect_equal(lizo_sep[["dual-find"]]$separation, lizo_sep[["dual-test"]]$separation)
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