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Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(testCompareR) > > test_check("testCompareR") WARNING: Zeros exist in contingency table. Tests may return NA/NaN. -------------------------------------------------------------------------------- CONTINGENCY TABLES -------------------------------------------------------------------------------- True Status - POSITIVE Test 2 Test 1 Positive Negative Positive 280 20 Negative 0 100 True Status - NEGATIVE Test 2 Test 1 Positive Negative Positive 45 10 Negative 0 145 Gold standard vs. Test 1 Test 1 Gold standard Positive Negative Positive 300 100 Negative 55 145 Gold standard vs. Test 2 Test 2 Gold standard Positive Negative Positive 280 120 Negative 45 155 -------------------------------------------------------------------------------- PREVALENCE (%) -------------------------------------------------------------------------------- Estimate SE Lower CI Upper CI Prevalence 66.7 1.9 62.8 70.3 -------------------------------------------------------------------------------- DIAGNOSTIC ACCURACIES -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI Sensitivity 75.0 2.2 70.5 79.0 Specificity 72.5 3.2 66.0 78.3 Test 2 (%) Estimate SE Lower CI Upper CI Sensitivity 70.0 2.3 65.4 74.3 Specificity 77.5 3.0 71.3 82.8 Global Null Hypothesis: Se1 = Se2 & Sp1 = Sp2 Test statistic: 31.57895 Adjusted p value: 4.167158e-07 ***SIGNIFICANT*** Investigating individual differences Null Hypothesis 1: Se1 = Se2 Test statistic: 18.05 Adjusted p value: 0.0001291072 ***SIGNIFICANT*** Null Hypothesis 2: Sp1 = Sp2 Test statistic: 8.1 Adjusted p value: 0.02213263 ***SIGNIFICANT*** -------------------------------------------------------------------------------- PREDICTIVE VALUES -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI PPV 84.5 1.9 80.4 87.9 NPV 59.2 3.1 52.9 65.2 Test 2 (%) Estimate SE Lower CI Upper CI PPV 86.2 1.9 82.0 89.5 NPV 56.4 3.0 50.5 62.1 Global Null Hypothesis: PPV1 = PPV2 & NPV1 = NPV2 Test statistic: 28.43169 Adjusted p value: 1.340192e-06 ***SIGNIFICANT*** Investigating individual differences Null Hypothesis 1: PPV1 = PPV2 Test statistic: 4.059529 Adjusted p value: 0.08784551 Null Hypothesis 2: NPV1 = NPV2 Test statistic: 6.343355 Adjusted p value: 0.04712873 ***SIGNIFICANT*** -------------------------------------------------------------------------------- LIKELIHOOD RATIOS -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI PLR 2.7 0.3 2.2 3.5 NLR 0.3 0.0 0.3 0.4 Test 2 (%) Estimate SE Lower CI Upper CI PLR 3.1 0.4 2.4 4.1 NLR 0.4 0.0 0.3 0.5 Global Null Hypothesis: PLR1 = PLR2 & NLR1 = NLR2 Test statistic: 24.2216 Adjusted p value: 5.499788e-06 ***SIGNIFICANT*** Investigating individual differences Null Hypothesis 1: PLR1 = PLR2 Test statistic: 2.013107 Adjusted p value: 0.08784551 Null Hypothesis 2: NLR1 = NLR2 Test statistic: 2.516314 Adjusted p value: 0.04712873 ***SIGNIFICANT*** WARNING: Tests have exactly equal performance. Tests may return NA/NaN. Zeros exist in contingency table. Tests may return NA/NaN. Youden Index of Test 1 is 0. Tests may return NA/NaN. Youden Index of Test 2 is 0. Tests may return NA/NaN. When Youden Index is less than or equal to zero a test returns the same proportion of positive results irrespective of true status. This indicates poor test performance. -------------------------------------------------------------------------------- CONTINGENCY TABLES -------------------------------------------------------------------------------- True Status - POSITIVE Test 2 Test 1 Positive Negative Positive 10 0 Negative 0 390 True Status - NEGATIVE Test 2 Test 1 Positive Negative Positive 190 0 Negative 0 10 Gold standard vs. Test 1 Test 1 Gold standard Positive Negative Positive 10 390 Negative 190 10 Gold standard vs. Test 2 Test 2 Gold standard Positive Negative Positive 10 390 Negative 190 10 -------------------------------------------------------------------------------- PREVALENCE (%) -------------------------------------------------------------------------------- Estimate SE Lower CI Upper CI Prevalence 66.7 1.9 62.8 70.3 -------------------------------------------------------------------------------- DIAGNOSTIC ACCURACIES -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI Sensitivity 2.5 0.8 1.3 4.5 Specificity 5.0 1.5 2.7 8.9 Test 2 (%) Estimate SE Lower CI Upper CI Sensitivity 2.5 0.8 1.3 4.5 Specificity 5.0 1.5 2.7 8.9 Global hypothesis testing was not or could not be performed. This is usually because: * prevalence is <10% and total number of participants < 100 * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. Individual tests have been attempted below. Investigating individual differences Null Hypothesis 1: Se1 = Se2 Test statistic: Inf Adjusted p value: 0 ***SIGNIFICANT*** Null Hypothesis 2: Sp1 = Sp2 Test statistic: Inf Adjusted p value: 0 ***SIGNIFICANT*** -------------------------------------------------------------------------------- PREDICTIVE VALUES -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI PPV 5.0 1.5 2.7 8.9 NPV 2.5 0.8 1.3 4.5 Test 2 (%) Estimate SE Lower CI Upper CI PPV 5.0 1.5 2.7 8.9 NPV 2.5 0.8 1.3 4.5 Global hypothesis testing was not or could not be performed. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. Individual tests have been attempted below. Investigating individual differences Null Hypothesis 1: PPV1 = PPV2 Test statistic: NaN Adjusted p value: NaN NAs or NaNs in individual tests. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. Null Hypothesis 2: NPV1 = NPV2 Test statistic: NaN Adjusted p value: NaN NAs or NaNs in individual tests. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. -------------------------------------------------------------------------------- LIKELIHOOD RATIOS -------------------------------------------------------------------------------- Test 1 (%) Estimate SE Lower CI Upper CI PLR 0.0 0 0.0 0.0 NLR 19.5 6 10.9 33.8 Test 2 (%) Estimate SE Lower CI Upper CI PLR 0.0 0 0.0 0.0 NLR 19.5 6 10.9 33.8 Global hypothesis testing was not or could not be performed. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. Individual tests have been attempted below. Investigating individual differences Null Hypothesis 1: PLR1 = PLR2 Test statistic: NaN Adjusted p value: NaN NAs or NaNs in individual tests. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests. Null Hypothesis 2: NLR1 = NLR2 Test statistic: NaN Adjusted p value: NaN NAs or NaNs in individual tests. This is usually because: * tests have identical performance * there are many zeros in the contingency table * Youden Index is < 0 Consider the quality of your data and/or tests.[ FAIL 0 | WARN 0 | SKIP 0 | PASS 561 ] > > proc.time() user system elapsed 3.23 0.62 3.86