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Type 'q()' to quit R. > library(testthat) > library(predRupdate) > > test_check("predRupdate") $OE_ratio [1] 1.900612 $OE_ratio_lower [1] 1.836826 $OE_ratio_upper [1] 1.966614 $CalInt [1] 0.7323461 $CalInt_SE NULL $CalInt_lower [1] 0.6920664 $CalInt_upper [1] 0.7726258 $CalSlope [1] 0.6483813 $CalSlope_SE NULL $CalSlope_lower [1] 0.5576126 $CalSlope_upper [1] 0.7391501 $AUC [1] 0.5814277 $AUC_SE NULL $AUC_lower [1] 0.570181 $AUC_upper [1] 0.5926743 $R2_CoxSnell NULL $R2_Nagelkerke [1] -0.08631391 $BrierScore [1] 0.1248575 $Brier_lower [1] 0.1218626 $Brier_upper [1] 0.1278525 Performance Results for Model 1 ================================= $OE_ratio [1] 1.900612 $OE_ratio_lower [1] 1.836826 $OE_ratio_upper [1] 1.966614 $CalInt [1] 0.7323461 $CalInt_SE NULL $CalInt_lower [1] 0.6920664 $CalInt_upper [1] 0.7726258 $CalSlope [1] 0.6483813 $CalSlope_SE NULL $CalSlope_lower [1] 0.5576126 $CalSlope_upper [1] 0.7391501 $AUC [1] 0.5814277 $AUC_SE NULL $AUC_lower [1] 0.570181 $AUC_upper [1] 0.5926743 $R2_CoxSnell NULL $R2_Nagelkerke [1] -0.08631391 $BrierScore [1] 0.1248575 $Brier_lower [1] 0.1218626 $Brier_upper [1] 0.1278525 Performance Results for Model 2 ================================= $OE_ratio [1] 0.8945127 $OE_ratio_lower [1] 0.8644921 $OE_ratio_upper [1] 0.9255758 $CalInt [1] -0.1325477 $CalInt_SE NULL $CalInt_lower [1] -0.1725205 $CalInt_upper [1] -0.09257488 $CalSlope [1] 0.9867769 $CalSlope_SE NULL $CalSlope_lower [1] 0.8488914 $CalSlope_upper [1] 1.124663 $AUC [1] 0.5828299 $AUC_SE NULL $AUC_lower [1] 0.5715523 $AUC_upper [1] 0.5941076 $R2_CoxSnell NULL $R2_Nagelkerke [1] 0.01322455 $BrierScore [1] 0.120598 $Brier_lower [1] 0.1172069 $Brier_upper [1] 0.1239891 Performance Results for Model 3 ================================= $OE_ratio [1] 1.594518 $OE_ratio_lower [1] 1.541004 $OE_ratio_upper [1] 1.649889 $CalInt [1] 0.5323554 $CalInt_SE NULL $CalInt_lower [1] 0.4923184 $CalInt_upper [1] 0.5723925 $CalSlope [1] 0.7211673 $CalSlope_SE NULL $CalSlope_lower [1] 0.5980537 $CalSlope_upper [1] 0.844281 $AUC [1] 0.5612504 $AUC_SE NULL $AUC_lower [1] 0.5497045 $AUC_upper [1] 0.5727963 $R2_CoxSnell NULL $R2_Nagelkerke [1] -0.04464768 $BrierScore [1] 0.1234254 $Brier_lower [1] 0.1202473 $Brier_upper [1] 0.1266034 Performance Results for Model 1 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 1.9006 1.8368 Calibration Intercept 0.7323 0.6921 Calibration Slope 0.6484 0.5576 Upper 95% Confidence Interval Observed:Expected Ratio 1.9666 Calibration Intercept 0.7726 Calibration Slope 0.7392 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval AUC 0.5814 0.5702 0.5927 Overall Performance Measures --------------------------------- Cox-Snell R-squared: -0.0481 Nagelkerke R-squared: -0.0863 Brier Score (CI): 0.1249 (0.1219, 0.1279) Also examine the distribution plot of predicted risks. Performance Results for Model 2 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 0.8945 0.8645 Calibration Intercept -0.1325 -0.1725 Calibration Slope 0.9868 0.8489 Upper 95% Confidence Interval Observed:Expected Ratio 0.9256 Calibration Intercept -0.0926 Calibration Slope 1.1247 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval AUC 0.5828 0.5716 0.5941 Overall Performance Measures --------------------------------- Cox-Snell R-squared: 0.0074 Nagelkerke R-squared: 0.0132 Brier Score (CI): 0.1206 (0.1172, 0.124) Also examine the distribution plot of predicted risks. Performance Results for Model 3 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 1.5945 1.5410 Calibration Intercept 0.5324 0.4923 Calibration Slope 0.7212 0.5981 Upper 95% Confidence Interval Observed:Expected Ratio 1.6499 Calibration Intercept 0.5724 Calibration Slope 0.8443 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval AUC 0.5613 0.5497 0.5728 Overall Performance Measures --------------------------------- Cox-Snell R-squared: -0.0249 Nagelkerke R-squared: -0.0446 Brier Score (CI): 0.1234 (0.1202, 0.1266) Also examine the distribution plot of predicted risks. $OE_ratio [1] 0.6319298 $OE_ratio_lower [1] 0.6211444 $OE_ratio_upper [1] 0.6429026 $CalSlope [1] 1.075666 $CalSlope_SE [1] 0.03890795 $CalSlope_lower [1] 0.9994074 $CalSlope_upper [1] 1.151924 $harrell_C [1] 0.586872 $harrell_C_SE [1] 0.003204527 $harrell_C_lower [1] 0.5805913 $harrell_C_upper [1] 0.5931528 Performance Results for Model 1 ================================= $OE_ratio [1] 1.220094 $OE_ratio_lower [1] 1.19927 $OE_ratio_upper [1] 1.241279 $CalSlope [1] 0.712948 $CalSlope_SE [1] 0.02804621 $CalSlope_lower [1] 0.6579785 $CalSlope_upper [1] 0.7679176 $harrell_C [1] 0.5789097 $harrell_C_SE [1] 0.003222861 $harrell_C_lower [1] 0.5725931 $harrell_C_upper [1] 0.5852264 Performance Results for Model 2 ================================= $OE_ratio [1] 0.6319298 $OE_ratio_lower [1] 0.6211444 $OE_ratio_upper [1] 0.6429026 $CalSlope [1] 1.075666 $CalSlope_SE [1] 0.03890795 $CalSlope_lower [1] 0.9994074 $CalSlope_upper [1] 1.151924 $harrell_C [1] 0.586872 $harrell_C_SE [1] 0.003204527 $harrell_C_lower [1] 0.5805913 $harrell_C_upper [1] 0.5931528 Performance Results for Model 3 ================================= $OE_ratio [1] 1.042847 $OE_ratio_lower [1] 1.025048 $OE_ratio_upper [1] 1.060955 $CalSlope [1] 0.9129803 $CalSlope_SE [1] 0.03682359 $CalSlope_lower [1] 0.8408074 $CalSlope_upper [1] 0.9851532 $harrell_C [1] 0.5767671 $harrell_C_SE [1] 0.003232409 $harrell_C_lower [1] 0.5704317 $harrell_C_upper [1] 0.5831025 Performance Results for Model 1 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 1.2201 1.1993 Calibration Slope 0.7129 0.6580 Upper 95% Confidence Interval Observed:Expected Ratio 1.2413 Calibration Slope 0.7679 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval Harrell C 0.5789 0.5726 0.5852 Also examine the distribution plot of predicted risks. Performance Results for Model 2 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 0.6319 0.6211 Calibration Slope 1.0757 0.9994 Upper 95% Confidence Interval Observed:Expected Ratio 0.6429 Calibration Slope 1.1519 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval Harrell C 0.5869 0.5806 0.5932 Also examine the distribution plot of predicted risks. Performance Results for Model 3 ================================= Calibration Measures --------------------------------- Estimate Lower 95% Confidence Interval Observed:Expected Ratio 1.0428 1.0250 Calibration Slope 0.9130 0.8408 Upper 95% Confidence Interval Observed:Expected Ratio 1.0610 Calibration Slope 0.9852 Also examine the calibration plot, if produced. Discrimination Measures --------------------------------- Estimate Lower 95% Confidence Interval Upper 95% Confidence Interval Harrell C 0.5768 0.5704 0.5831 Also examine the distribution plot of predicted risks. [ FAIL 0 | WARN 0 | SKIP 4 | PASS 231 ] ══ Skipped tests (4) ═══════════════════════════════════════════════════════════ • On CRAN (4): 'test-pred_stacked_regression.R:24:3', 'test-pred_validate_logistic.R:29:3', 'test-pred_validate_survival.R:22:3', 'test-summary_predinfo.R:8:3' [ FAIL 0 | WARN 0 | SKIP 4 | PASS 231 ] > > proc.time() user system elapsed 18.32 1.82 20.17