tests/testthat/test-lm.R

In contrast: A Collection of Contrast Methods

context("lm models")

# ------------------------------------------------------------------------------
library(splines)

lm_fit_1 <- lm(mpg ~ (wt + am), data = mtcars)
lm_fit_2 <- lm(expression ~ ., data = two_factor_crossed)
lm_fit_3 <- lm(mpg ~ ns(wt, 2) + am, data = mtcars)

summary_1 <- summary(lm_fit_1)
summary_2 <- summary(lm_fit_2)
summary_3 <- summary(lm_fit_3)

anova_1 <- anova(lm_fit_1)
anova_2 <- anova(lm_fit_2)
anova_3 <- anova(lm_fit_3)

test_that("all numeric", {
    a_1 <- list(am = 0, wt = 2)
    b_1 <- list(am = 1, wt = 2)
    c_1 <- contrast(lm_fit_1, a_1, b_1)
    expect_equivalent(
        summary_1$coefficients["am", "Pr(>|t|)"],
        c_1$Pvalue
    )

    # bad inputs
    a_2 <- list(am = "a", wt = 2)
    b_2 <- list(am = "b", wt = 2)
    expect_error(
        contrast(lm_fit_1, a_2, b_2),
        "variable 'am' was fitted with type \"numeric\" but type \"factor\""
    )
})

test_that("numeric and factor", {
    a_3 <- list(diet = "low fat", group = "vehicle")
    b_3 <- list(diet = "high fat", group = "vehicle")
    c_3 <- contrast(lm_fit_2, a_3, b_3)
    expect_equivalent(
        summary_2$coefficients["dietlow fat", "Pr(>|t|)"],
        c_3$Pvalue
    )
    a_4 <- list(diet = "low fat", group = "vehicle")
    b_4 <- list(diet = "low fat", group = "treatment")
    c_4 <- contrast(lm_fit_2, a_4, b_4)
    expect_equivalent(
        summary_2$coefficients["groupvehicle", "Pr(>|t|)"],
        c_4$Pvalue
    )
})

test_that("function in formula works as expected", {
    a_5 <- list(am = 0, wt = 2)
    b_5 <- list(am = 1, wt = 2)
    c_5 <- contrast(lm_fit_3, a_5, b_5)
    expect_equivalent(
        summary_3$coefficients["am", "Pr(>|t|)"],
        c_5$Pvalue
    )

    # bad inputs
    a_6 <- list(am = "a", wt = 2)
    b_6 <- list(am = "b", wt = 2)
    expect_error(
        contrast(lm_fit_3, a_6, b_6),
        "variable 'am' was fitted with type \"numeric\" but type \"factor\""
    )
})