Nothing
coef_tol <- 1e-4
if (requireNamespace("prefmod", quietly = TRUE) &
require("survival")) {
test_that("PLADMM anova matches rank ordered logit model [salad]", {
## setting rho ~ 10% log-lik gives good results (not extensively tested!)
res0_PLADMM <- pladmm(salad_rankings, ~ acetic + gluconic,
data = features, rho = 8, rtol = 1e-5)
res1_PLADMM <- pladmm(salad_rankings, ~ acetic,
data = features, rho = 8, rtol = 1e-5)
res0_RO <- coxph(Surv(ranking, status) ~
acetic + gluconic + strata(chid),
data = cbind(salad_long_rankings, status = 1))
res1_RO <- coxph(Surv(ranking, status) ~
acetic + strata(chid),
data = cbind(salad_long_rankings, status = 1))
## expect that anova equivalent for list of models
anova1 <- anova(res0_PLADMM, res1_PLADMM)
anova2 <- anova(res0_RO, res1_RO) # tables log-likelihood vs deviance
expect_equal(anova1$Deviance, #difference in residual deviance
anova2$Chisq, #Chi-squared statistic
tolerance = coef_tol)
expect_equal(anova1$Df, anova2$Df)
id <- grep("Pr?(>|Chi|)", names(anova2)) # name changed in survival 3.4.0
expect_equal(anova1$`Pr(>Chi)`, #difference in residual deviance
anova2[, id], #Chi-squared statistic
tolerance = coef_tol)
## expect that anova equivalent for single model
anova1 <- anova(res0_PLADMM)
anova2 <- anova(res0_RO) # tables log-likelihood vs deviance
expect_equal(anova1$Deviance, #difference in residual deviance
anova2$Chisq, #Chi-squared statistic
tolerance = coef_tol)
expect_equal(anova1$Df, anova2$Df)
expect_equal(anova1$`Pr(>Chi)`, #difference in residual deviance
anova2$`Pr(>|Chi|)`, #Chi-squared statistic
tolerance = coef_tol)
})
}
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