skip_on_os(c("mac", "solaris")) skip_if_not_installed("marginaleffects") skip_if(getRversion() < "4.3.0") data(efc, package = "ggeffects") efc$c172code <- as.factor(efc$c172code) m1 <- lm(neg_c_7 ~ c12hour * barthtot * c172code, data = efc) m2 <- lm(c12hour ~ neg_c_7 * barthtot, data = efc) m3 <- lm(neg_c_7 ~ c12hour * barthtot, data = efc) states <- as.data.frame(state.x77) states$HSGrad <- states$`HS Grad` m4 <- lm(Income ~ HSGrad + Murder * Illiteracy, data = states ) test_that("ggpredict, johnson_neyman, 2 focal terms, one direction", { pr <- ggpredict(m1, c("c12hour", "barthtot")) out <- utils::capture.output(print(johnson_neyman(pr, precision = 100))) expect_identical( out, c( "The association between `c12hour` and `neg_c_7` is negative for values", " of `barthtot` lower than 47. There were no clear associations for values", " of `barthtot` higher than 47." ) ) }) test_that("ggpredict, johnson_neyman, 2 focal terms, inside interval", { pr <- ggpredict(m2, c("neg_c_7", "barthtot")) out <- utils::capture.output(print(johnson_neyman(pr, precision = 100))) expect_identical( out, c( "The association between `neg_c_7` and `c12hour` is positive for values", " of `barthtot` that range from 46 to 49. Outside of this interval, there", " were no clear associations." ) ) }) test_that("ggpredict, johnson_neyman, 2 focal terms, one direction", { pr <- ggpredict(m3, c("c12hour", "barthtot")) out <- utils::capture.output(print(johnson_neyman(pr, precision = 100))) expect_identical( out, c( "The association between `c12hour` and `neg_c_7` is positive for values", " of `barthtot` higher than 48. There were no clear associations for", " values of `barthtot` lower than 48." ) ) }) test_that("ggpredict, johnson_neyman, 2 focal terms, outside interval", { pr <- ggpredict(m4, c("Murder", "Illiteracy")) out <- utils::capture.output(print(johnson_neyman(pr, precision = 100))) expect_identical( out, c( "The association between `Murder` and `Income` is positive for values of", " `Illiteracy` lower than 0.78 and negative for values higher than 2.66.", " Inside the interval of [0.78, 2.66], there were no clear associations." ) ) }) test_that("ggpredict, johnson_neyman, 3 focal terms", { pr <- ggpredict(m1, c("c12hour", "c172code", "barthtot")) out <- utils::capture.output(print(johnson_neyman(pr, precision = 100))) expect_identical( out, c( "# Level `c172code = 1`", "The association between `c12hour` and `neg_c_7` is negative for values", " of `barthtot` lower than 47. There were no clear associations for values", " of `barthtot` higher than 47.", "", "# Level `c172code = 2`", "The association between `c12hour` and `neg_c_7` is positive for values", " of `barthtot` higher than 33. There were no clear associations for", " values of `barthtot` lower than 33.", "", "# Level `c172code = 3`", "There are no clear negative or positive associations between `c12hour`", " and `neg_c_7` for any value of `barthtot`." ) ) }) test_that("ggpredict, johnson_neyman, p-adjustment", { pr <- ggpredict(m1, c("c12hour", "barthtot")) out1 <- johnson_neyman(pr, p_adjust = "es", precision = 100) out2 <- johnson_neyman(pr, precision = 100) out3 <- johnson_neyman(pr, p_adjust = "bh", precision = 100) expect_identical(attributes(out1)$intervals$pos_lower, 38) expect_identical(attributes(out2)$intervals$pos_lower, 47) expect_identical(attributes(out3)$intervals$pos_lower, 38) out <- utils::capture.output(print(out1)) expect_identical( out, c( "The association between `c12hour` and `neg_c_7` is negative for values", " of `barthtot` lower than 38. There were no clear associations for values", " of `barthtot` higher than 38.", "", "P-values were adjusted using the Esarey & Sumner (2017) method." ) ) out <- utils::capture.output(print(out3)) expect_identical( out, c( "The association between `c12hour` and `neg_c_7` is negative for values", " of `barthtot` lower than 38. There were no clear associations for values", " of `barthtot` higher than 38.", "", "P-values were adjusted using the Benjamini & Hochberg (1995) method." ) ) expect_error(johnson_neyman(pr, p_adjust = "bonferroni"), regex = "be one of") }) test_that("ggpredict, johnson_neyman, p-adjustment, glm", { data(efc, package = "ggeffects") efc$neg_c_7d <- as.numeric(efc$neg_c_7 > median(efc$neg_c_7, na.rm = TRUE)) d <- efc fit <- glm(neg_c_7d ~ c12hour * barthtot, data = d, family = binomial(link = "logit")) pr <- ggpredict(fit, terms = c("c12hour", "barthtot"), verbose = FALSE) out1 <- johnson_neyman(pr, p_adjust = "es", precision = 100) out2 <- johnson_neyman(pr, precision = 100) out3 <- johnson_neyman(pr, p_adjust = "bh", precision = 100) expect_identical(attributes(out1)$intervals$pos_lower, NA_real_) expect_identical(attributes(out2)$intervals$pos_lower, 68) expect_identical(attributes(out3)$intervals$pos_lower, NA_real_) out <- utils::capture.output(print(out1)) expect_identical( out, c( "There are no clear negative or positive associations between `c12hour`", " and `neg_c_7d` for any value of `barthtot`.", "", "P-values were adjusted using the Esarey & Sumner (2017) method." ) ) }) test_that("ggpredict, johnson_neyman, p-adjustment, df and vcov", { data(efc, package = "ggeffects") efc$c172code <- as.factor(efc$c172code) m1 <- lm(neg_c_7 ~ c12hour * barthtot * c172code, data = efc) pr <- ggpredict(m1, c("c12hour", "barthtot")) out1 <- johnson_neyman(pr, precision = 100) out2 <- johnson_neyman(pr, p_adjust = "esarey", precision = 100) out3 <- johnson_neyman(pr, p_adjust = "esarey", df = 100, precision = 100) out4 <- johnson_neyman(pr, p_adjust = "esarey", vcov = "HC1", precision = 100) out5 <- johnson_neyman(pr, p_adjust = "esarey", vcov = "HC1", df = 100, precision = 100) expect_equal( head(out1$conf.low), c(-0.04875, -0.04811, -0.04748, -0.04685, -0.04622, -0.04559), tolerance = 1e-3 ) expect_equal( head(out2$conf.low), c(-0.05278, -0.05209, -0.0514, -0.05071, -0.05003, -0.04935), tolerance = 1e-3 ) expect_equal( head(out3$conf.low), c(-0.05329, -0.0526, -0.0519, -0.05121, -0.05052, -0.04983), tolerance = 1e-3 ) expect_equal( head(out4$conf.low), c(-0.05465, -0.05397, -0.05329, -0.05261, -0.05193, -0.05126), tolerance = 1e-3 ) expect_equal( head(out5$conf.low), c(-0.0552, -0.05452, -0.05383, -0.05314, -0.05246, -0.05178), tolerance = 1e-3 ) })