suppressMessages(library(dplyr)) # data from CMH-17-1G Section 8.3.11.1.1 cmh_17_8_3_11_1_1 <- tribble( ~batch, ~strength, ~condition, "A", 118.3774604, "CTD", "A", 84.9581364, "RTD", "A", 83.7436035, "ETD", "A", 123.6035612, "CTD", "A", 92.4891822, "RTD", "A", 84.3831677, "ETD", "A", 115.2238092, "CTD", "A", 96.8212659, "RTD", "A", 94.8030433, "ETD", "A", 112.6379744, "CTD", "A", 109.030325, "RTD", "A", 94.3931537, "ETD", "A", 116.5564277, "CTD", "A", 97.8212659, "RTD", "A", 101.702222, "ETD", "A", 123.1649896, "CTD", "A", 100.921519, "RTD", "A", 86.5372121, "ETD", "B", 128.5589027, "CTD", "A", 103.699444, "RTD", "A", 92.3772684, "ETD", "B", 113.1462103, "CTD", "B", 93.7908212, "RTD", "B", 89.2084024, "ETD", "B", 121.4248107, "CTD", "B", 107.526709, "RTD", "B", 100.686001, "ETD", "B", 134.3241906, "CTD", "B", 94.5769704, "RTD", "B", 81.0444192, "ETD", "B", 129.6405117, "CTD", "B", 93.8831373, "RTD", "B", 91.3398070, "ETD", "B", 117.9818658, "CTD", "B", 98.2296605, "RTD", "B", 93.1441939, "ETD", "C", 115.4505226, "CTD", "B", 111.346590, "RTD", "B", 85.8204168, "ETD", "C", 120.0369467, "CTD", "B", 100.817538, "RTD", "C", 94.8966273, "ETD", "C", 117.1631088, "CTD", "C", 100.382203, "RTD", "C", 95.8068520, "ETD", "C", 112.9302797, "CTD", "C", 91.5037811, "RTD", "C", 86.7842252, "ETD", "C", 117.9114501, "CTD", "C", 100.083233, "RTD", "C", 94.4011973, "ETD", "C", 120.1900159, "CTD", "C", 95.6393615, "RTD", "C", 96.7231171, "ETD", "C", 110.7295966, "CTD", "C", 109.304779, "RTD", "C", 89.9010384, "ETD", "C", 100.078562, "RTD", "C", 99.1205847, "RTD", "C", 89.3672306, "ETD", "A", 106.357525, "ETW", "A", 99.0239966, "ETW2", "A", 105.898733, "ETW", "A", 103.341238, "ETW2", "A", 88.4640082, "ETW", "A", 100.302130, "ETW2", "A", 103.901744, "ETW", "A", 98.4634133, "ETW2", "A", 80.2058219, "ETW", "A", 92.2647280, "ETW2", "A", 109.199597, "ETW", "A", 103.487693, "ETW2", "A", 61.0139431, "ETW", "A", 113.734763, "ETW2", "B", 99.3207107, "ETW", "B", 108.172659, "ETW2", "B", 115.861770, "ETW", "B", 108.426732, "ETW2", "B", 82.6133082, "ETW", "B", 116.260375, "ETW2", "B", 85.3690411, "ETW", "B", 121.049610, "ETW2", "B", 115.801622, "ETW", "B", 111.223082, "ETW2", "B", 44.3217741, "ETW", "B", 104.574843, "ETW2", "B", 117.328077, "ETW", "B", 103.222552, "ETW2", "B", 88.6782903, "ETW", "C", 99.3918538, "ETW2", "C", 107.676986, "ETW", "C", 87.3421658, "ETW2", "C", 108.960241, "ETW", "C", 102.730741, "ETW2", "C", 116.122640, "ETW", "C", 96.3694916, "ETW2", "C", 80.2334815, "ETW", "C", 99.5946088, "ETW2", "C", 106.145570, "ETW", "C", 97.0712407, "ETW2", "C", 104.667866, "ETW", "C", 104.234953, "ETW" ) test_that("expected diagnostic failures are noted for pooling methods", { # This test follows CMH-17-1G Section # This section in CMH-17-1G shows the removal of one condition # before running Levene's test on the pooled data, so this test # will be skipped in this test. expect_warning( expect_warning( expect_warning( expect_warning( expect_warning( res <- basis_pooled_sd(cmh_17_8_3_11_1_1, strength, condition, batch), "outliers_within_batch" ), "between_group_variability" ), "outliers_within_group" ), "pooled_data_normal" ), "pooled_variance_equal" ) expect_length(res$diagnostic_obj$outliers_within_batch, 5) expect_length(res$diagnostic_obj$outliers_within_batch$RTD, 3) expect_equal(class(res$diagnostic_obj$outliers_within_batch$CTD$A), "mnr") expect_equal(res$diagnostic_obj$outliers_within_batch$CTD$A$n_outliers, 0) expect_length(res$diagnostic_obj$between_group_variability, 5) expect_equal(class(res$diagnostic_obj$between_group_variability$RTD), "adk") expect_false( res$diagnostic_obj$between_group_variability$RTD$reject_same_dist) expect_length(res$diagnostic_obj$outliers_within_group, 5) expect_equal(class(res$diagnostic_obj$outliers_within_group$CTD), "mnr") expect_equal(res$diagnostic_obj$outliers_within_group$CTD$n_outliers, 0) expect_equal(class(res$diagnostic_obj$pooled_data_normal), "anderson_darling") expect_true(res$diagnostic_obj$pooled_data_normal$reject_distribution) expect_equal(class(res$diagnostic_obj$pooled_variance_equal), "levene") expect_true(res$diagnostic_obj$pooled_variance_equal$reject_equal_variance) expect_warning( expect_warning( expect_warning( expect_warning( res <- cmh_17_8_3_11_1_1 %>% filter(condition != "ETW2") %>% basis_pooled_sd(strength, condition, batch), "outliers_within_batch" ), "outliers_within_group" ), "pooled_data_normal" ), "pooled_variance_equal" ) # removing both ETW and ETW2 should remove all diagnostic failures res <- cmh_17_8_3_11_1_1 %>% filter(condition != "ETW2" & condition != "ETW") %>% basis_pooled_sd(strength, condition, batch) expect_equal(res$basis$value[res$basis$group == "CTD"], 108.70, tolerance = 0.02) expect_equal(res$basis$value[res$basis$group == "RTD"], 88.52, tolerance = 0.02) expect_equal(res$basis$value[res$basis$group == "ETD"], 80.68, tolerance = 0.02) expect_warning( expect_warning( expect_warning( expect_warning( expect_warning( res <- basis_pooled_cv(cmh_17_8_3_11_1_1, strength, condition, batch), "outliers_within_batch" ), "between_group_variability" ), "outliers_within_group" ), "pooled_data_normal" ), "normalized_variance_equal" ) expect_warning( expect_warning( expect_warning( expect_warning( res <- cmh_17_8_3_11_1_1 %>% filter(condition != "ETW2") %>% basis_pooled_cv(strength, condition, batch), "outliers_within_batch" ), "outliers_within_group" ), "pooled_data_normal" ), "normalized_variance_equal" ) # removing both ETW and ETW2 should remove all diagnostic failures res <- cmh_17_8_3_11_1_1 %>% filter(condition != "ETW2" & condition != "ETW") %>% basis_pooled_cv(strength, condition, batch) }) # data from CMH-17-1G Section 8.3.11.1.2 poolable_data <- tribble( ~batch, ~strength, ~condition, 1, 79.04517, "CTD", 1, 102.6014, "CTD", 1, 97.79372, "CTD", 1, 92.86423, "CTD", 1, 117.218, "CTD", 1, 108.7168, "CTD", 1, 112.2773, "CTD", 1, 114.0129, "CTD", 2, 106.8452, "CTD", 2, 112.3911, "CTD", 2, 115.5658, "CTD", 2, 87.40657, "CTD", 2, 102.2785, "CTD", 2, 110.6073, "CTD", 3, 105.2762, "CTD", 3, 110.8924, "CTD", 3, 108.7638, "CTD", 3, 110.9833, "CTD", 3, 101.3417, "CTD", 3, 100.0251, "CTD", 1, 103.2006, "RTD", 1, 105.1034, "RTD", 1, 105.1893, "RTD", 1, 100.4189, "RTD", 2, 85.32319, "RTD", 2, 92.69923, "RTD", 2, 98.45242, "RTD", 2, 104.1014, "RTD", 2, 91.51841, "RTD", 2, 101.3746, "RTD", 2, 101.5828, "RTD", 2, 99.57384, "RTD", 2, 88.84826, "RTD", 3, 92.18703, "RTD", 3, 101.8234, "RTD", 3, 97.68909, "RTD", 3, 101.5172, "RTD", 3, 100.0481, "RTD", 3, 102.0544, "RTD", 1, 63.22764, "ETW", 1, 70.84454, "ETW", 1, 66.43223, "ETW", 1, 75.37771, "ETW", 1, 72.43773, "ETW", 1, 68.43073, "ETW", 1, 69.72524, "ETW", 2, 66.20343, "ETW", 2, 60.51251, "ETW", 2, 65.69334, "ETW", 2, 62.73595, "ETW", 2, 59.00798, "ETW", 2, 62.37761, "ETW", 3, 64.3947, "ETW", 3, 72.8491, "ETW", 3, 66.56226, "ETW", 3, 66.56779, "ETW", 3, 66.00123, "ETW", 3, 59.62108, "ETW", 3, 60.61167, "ETW", 3, 57.65487, "ETW", 3, 66.51241, "ETW", 3, 64.89347, "ETW", 3, 57.73054, "ETW", 3, 68.94086, "ETW", 3, 61.63177, "ETW", 1, 54.09806, "ETW2", 1, 58.87615, "ETW2", 1, 61.60167, "ETW2", 1, 60.23973, "ETW2", 1, 61.4808, "ETW2", 1, 64.55832, "ETW2", 2, 57.76131, "ETW2", 2, 49.91463, "ETW2", 2, 61.49271, "ETW2", 2, 57.7281, "ETW2", 2, 62.11653, "ETW2", 2, 62.69353, "ETW2", 3, 61.38523, "ETW2", 3, 60.39053, "ETW2", 3, 59.17616, "ETW2", 3, 60.17616, "ETW2", 3, 46.47396, "ETW2", 3, 51.16616, "ETW2" ) test_that("Pooled SD results match ASAP results", { # This data fails the anderson-darling test for normality for the # transformed data expect_warning( expect_message( expect_message( res_b <- basis_pooled_sd(poolable_data, strength, condition, override = c("pooled_variance_equal")), "outliers_within_batch" ), "between_group_variability" ), "pooled_data_normal" ) expect_equal(res_b$basis$value[res_b$basis$group == "CTD"], 93.64, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "RTD"], 87.30, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW"], 54.33, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW2"], 47.12, tolerance = 0.01) expect_equal(res_b$n, 83) expect_equal(res_b$r, 4) expect_output(print(res_b), "b-basis", ignore.case = TRUE) expect_output(print(res_b), "pooled standard deviation", ignore.case = TRUE) expect_output(print(res_b), "CTD.*93\\.6", ignore.case = TRUE) expect_output(print(res_b), "RTD.*87\\.29", ignore.case = TRUE) expect_output(print(res_b), "ETW.*54\\.3", ignore.case = TRUE) expect_output(print(res_b), "ETW2.*47\\.07", ignore.case = TRUE) res_a <- basis_pooled_sd(poolable_data, strength, condition, p = 0.99, conf = 0.95, override = c("pooled_data_normal", "pooled_variance_equal", "outliers_within_batch", "between_group_variability")) expect_equal(res_a$basis$value[res_a$basis$group == "CTD"], 86.19, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "RTD"], 79.86, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW"], 46.84, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW2"], 39.69, tolerance = 0.01) }) test_that("Pooled CV results match CMH17STATS", { # This data fails the anderson-darling test for normality for the # transformed data expect_warning( expect_message( expect_message( res_b <- basis_pooled_cv(poolable_data, strength, condition), "outliers_within_batch" ), "between_group_variability" ), "pooled_data_normal" ) expect_equal(res_b$basis$value[res_b$basis$group == "CTD"], 90.89, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "RTD"], 85.37, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW"], 56.79, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW2"], 50.55, tolerance = 0.01) expect_equal(res_b$n, 83) expect_equal(res_b$r, 4) expect_output(print(res_b), "b-basis", ignore.case = TRUE) expect_output(print(res_b), "pooled CV", ignore.case = TRUE) expect_output(print(res_b), "CTD.*90\\.8", ignore.case = TRUE) expect_output(print(res_b), "RTD.*85\\.3", ignore.case = TRUE) expect_output(print(res_b), "ETW.*56\\.7", ignore.case = TRUE) expect_output(print(res_b), "ETW2.*50\\.5", ignore.case = TRUE) expect_equal(class(res_b$diagnostic_obj$normalized_variance_equal), "levene") expect_false( res_b$diagnostic_obj$normalized_variance_equal$reject_equal_variance) res_a <- basis_pooled_cv(poolable_data, strength, condition, p = 0.99, conf = 0.95, override = c("pooled_data_normal", "outliers_within_batch", "between_group_variability")) expect_equal(res_a$basis$value[res_a$basis$group == "CTD"], 81.62, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "RTD"], 76.67, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW"], 50.98, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW2"], 45.40, tolerance = 0.01) expect_output(print(res_a), "a-basis", ignore.case = TRUE) }) test_that("Pooled data matches CMH17-STATS with mod CV, SD pooling", { # pooled SD modified CV results # pooled data fails Levene's test after mod CV transform # based on `poolable_data` dataset with ETW2 removed data <- filter(poolable_data, condition != "ETW2") res_b <- basis_pooled_sd(data, strength, condition, modcv = TRUE, override = c("pooled_variance_equal", "outliers_within_batch", "between_group_variability")) expect_equal(res_b$basis$value[res_b$basis$group == "CTD"], 92.25, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "RTD"], 85.91, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW"], 52.97, tolerance = 0.01) expect_output(print(res_b), "Modified CV") res_a <- basis_pooled_sd(data, strength, condition, p = 0.99, conf = 0.95, modcv = TRUE, override = c("pooled_variance_equal", "outliers_within_batch", "between_group_variability")) expect_equal(res_a$basis$value[res_a$basis$group == "CTD"], 83.81, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "RTD"], 77.48, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW"], 44.47, tolerance = 0.01) }) test_that("Pooled data matches CMH17-STATS with mod CV, CV pooling", { # pooled CV modified CV results # pooled data passes Levene's test after mod CV transform # based on `poolable_data` dataset with ETW2 removed data <- filter(poolable_data, condition != "ETW2") res_b <- basis_pooled_cv(data, strength, condition, modcv = TRUE, override = c("outliers_within_batch", "between_group_variability")) expect_equal(res_b$basis$value[res_b$basis$group == "CTD"], 90.31, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "RTD"], 84.83, tolerance = 0.01) expect_equal(res_b$basis$value[res_b$basis$group == "ETW"], 56.43, tolerance = 0.01) expect_output(print(res_b), "Modified CV") res_a <- basis_pooled_cv(data, strength, condition, p = 0.99, conf = 0.95, modcv = TRUE, override = c("outliers_within_batch", "between_group_variability")) expect_equal(res_a$basis$value[res_a$basis$group == "CTD"], 80.57, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "RTD"], 75.69, tolerance = 0.01) expect_equal(res_a$basis$value[res_a$basis$group == "ETW"], 50.33, tolerance = 0.01) }) test_that("glance for pooled methods works", { res <- carbon.fabric %>% filter(test == "WT") %>% basis_pooled_sd(strength, condition, batch, override = c("outliers_within_batch")) %>% glance(TRUE) # 3 conditions should produce 3 basis values and hence 3 rows expect_equal(nrow(res), 3) }) test_that("pooled methods process override='all'", { res <- basis_pooled_sd(poolable_data, strength, condition, modcv = TRUE, override = "all") expect_equal(res$override, c("outliers_within_batch", "between_group_variability", "outliers_within_group", "pooled_data_normal", "pooled_variance_equal")) expect_length(res$diagnostic_failures, 0) res <- basis_pooled_cv(poolable_data, strength, condition, modcv = TRUE, override = "all") expect_equal(res$override, c("outliers_within_batch", "between_group_variability", "outliers_within_group", "pooled_data_normal", "normalized_variance_equal")) expect_length(res$diagnostic_failures, 0) })