R Under development (unstable) (2024-07-28 r86931 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(adjustedCurves) > > library(dplyr) Attaching package: 'dplyr' The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union > > library(testthat) Attaching package: 'testthat' The following object is masked from 'package:dplyr': matches > library(vdiffr) > library(survival) > library(ggplot2) > library(Matching) Loading required package: MASS Attaching package: 'MASS' The following object is masked from 'package:dplyr': select ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## > library(WeightIt) > library(prodlim) > library(MASS) > library(tidyr) Attaching package: 'tidyr' The following object is masked from 'package:testthat': matches > library(riskRegression) riskRegression version 2023.12.21 > library(pec) Attaching package: 'pec' The following objects are masked from 'package:riskRegression': ipcw, selectCox > library(geepack) > library(nnet) > library(cmprsk) > library(eventglm) Attaching package: 'eventglm' The following objects are masked from 'package:prodlim': leaveOneOut.competing.risks, leaveOneOut.survival The following objects are masked from 'package:survival': colon, mgus2 > library(rmarkdown) > library(mice) Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind > > test_check("adjustedCurves") Loading required namespace: pammtools Loading required namespace: doParallel starting worker pid=127900 on localhost:11653 at 16:24:23.457 starting worker pid=42320 on localhost:11653 at 16:24:23.470 Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools starting worker pid=89272 on localhost:11653 at 16:24:29.481 starting worker pid=44208 on localhost:11653 at 16:24:29.499 Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools Warning message: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Loglik converged before variable 1,2 ; coefficient may be infinite. starting worker pid=118716 on localhost:11653 at 16:24:36.101 starting worker pid=26668 on localhost:11653 at 16:24:36.149 Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools starting worker pid=127648 on localhost:11653 at 16:24:41.385 starting worker pid=71900 on localhost:11653 at 16:24:41.389 Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Loading required package: adjustedCurves loaded adjustedCurves and set parent environment Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival Attaching package: 'mice' The following object is masked from 'package:stats': filter The following objects are masked from 'package:base': cbind, rbind Loading required package: survival Attaching package: 'survival' The following objects are masked from 'package:eventglm': colon, mgus2 Loading required package: prodlim Attaching package: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools riskRegression version 2023.12.21 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-14, Build Date: 2023-09-13) ## See https://www.jsekhon.com for additional documentation. ## Please cite software as: ## Jasjeet S. Sekhon. 2011. ``Multivariate and Propensity Score Matching ## Software with Automated Balance Optimization: The Matching package for R.'' ## Journal of Statistical Software, 42(7): 1-52. ## Attaching package: 'testthat' The following object is masked from 'package:tidyr': matches Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following object is masked from 'package:MASS': select The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: foreach Loading required package: rngtools Warning messages: Warning messages: 1: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :1: Ran out of iterations and did not converge 2: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Loglik converged before variable 1 ; coefficient may be infinite. Loglik converged before variable 1 ; coefficient may be infinite. 3: In ate_checkArgs(call = call, object.event = object.event, object.censor = object.censor, : Rare event 2: 4: In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. In ate_checkArgs(call = call, object.event = object.event, object.censor = object.censor, : Rare event 5: In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. 3: 6: In predictCoxPL(object = object, newdata = newdata, times = times, :In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. Estimated survival outside the range [0,1]. Consider using predictCox instead of predictCoxPL. Loading required namespace: cowplot Loading required namespace: ggpp Assuming "Treatment" is the treated level. If not, supply an argument to `focal`. [ FAIL 0 | WARN 4 | SKIP 170 | PASS 1688 ] ══ Skipped tests (170) ═════════════════════════════════════════════════════════ • On CRAN (170): 'test_adjusted_curve_test.r:45:3', 'test_adjusted_curve_test.r:91:3', 'test_adjusted_curve_test.r:137:3', 'test_adjusted_curve_test.r:183:3', 'test_adjustedcif.method_S3.r:16:3', 'test_adjustedcif.method_S3.r:20:3', 'test_adjustedcif_S3.r:18:3', 'test_adjustedcif_S3.r:22:3', 'test_adjustedcif_S3.r:27:3', 'test_adjustedcif_S3.r:32:3', 'test_adjustedcif_S3.r:37:3', 'test_adjustedcif_S3.r:42:3', 'test_adjustedcif_S3.r:47:3', 'test_adjustedcif_S3.r:52:3', 'test_adjustedcif_S3.r:57:3', 'test_adjustedcif_S3.r:62:3', 'test_adjustedcif_S3.r:68:3', 'test_adjustedcif_S3.r:74:3', 'test_adjustedcif_S3.r:80:3', 'test_adjustedsurv.method_S3.r:15:3', 'test_adjustedsurv.method_S3.r:19:3', 'test_adjustedsurv_S3.r:17:3', 'test_adjustedsurv_S3.r:21:3', 'test_adjustedsurv_S3.r:26:3', 'test_adjustedsurv_S3.r:31:3', 'test_adjustedsurv_S3.r:36:3', 'test_adjustedsurv_S3.r:41:3', 'test_adjustedsurv_S3.r:46:3', 'test_adjustedsurv_S3.r:51:3', 'test_adjustedsurv_S3.r:56:3', 'test_adjustedsurv_S3.r:61:3', 'test_adjustedsurv_S3.r:66:3', 'test_adjustedsurv_S3.r:71:3', 'test_adjustedsurv_S3.r:76:3', 'test_adjustedsurv_S3.r:81:3', 'test_adjustedsurv_S3.r:86:3', 'test_adjustedsurv_S3.r:91:3', 'test_adjustedsurv_S3.r:96:3', 'test_adjustedsurv_S3.r:101:3', 'test_adjustedsurv_S3.r:107:3', 'test_adjustedsurv_S3.r:113:3', 'test_adjustedsurv_S3.r:119:3', 'test_curve_test_S3.r:21:3', 'test_curve_test_S3.r:25:3', 'test_plot.adjustedcif.r:22:3', 'test_plot.adjustedcif.r:28:3', 'test_plot.adjustedcif.r:34:3', 'test_plot.adjustedcif.r:40:3', 'test_plot.adjustedcif.r:50:3', 'test_plot.adjustedcif.r:61:3', 'test_plot.adjustedcif.r:76:3', 'test_plot.adjustedcif.r:92:3', 'test_plot.adjustedcif.r:100:3', 'test_plot.adjustedcif.r:106:3', 'test_plot.adjustedcif.r:112:3', 'test_plot.adjustedcif.r:118:3', 'test_plot.adjustedcif.r:124:3', 'test_plot.adjustedcif.r:131:3', 'test_plot.adjustedcif.r:137:3', 'test_plot.adjustedcif.r:143:3', 'test_plot.adjustedcif.r:154:3', 'test_plot.adjustedcif.r:160:3', 'test_plot.adjustedcif.r:166:3', 'test_plot.adjustedcif.r:173:3', 'test_plot.adjustedcif.r:179:3', 'test_plot.adjustedcif.r:185:3', 'test_plot.adjustedcif.r:192:3', 'test_plot.adjustedcif.r:221:3', 'test_plot.adjustedsurv.r:38:3', 'test_plot.adjustedsurv.r:44:3', 'test_plot.adjustedsurv.r:50:3', 'test_plot.adjustedsurv.r:56:3', 'test_plot.adjustedsurv.r:66:3', 'test_plot.adjustedsurv.r:77:3', 'test_plot.adjustedsurv.r:92:3', 'test_plot.adjustedsurv.r:108:3', 'test_plot.adjustedsurv.r:120:3', 'test_plot.adjustedsurv.r:126:3', 'test_plot.adjustedsurv.r:132:3', 'test_plot.adjustedsurv.r:138:3', 'test_plot.adjustedsurv.r:144:3', 'test_plot.adjustedsurv.r:150:3', 'test_plot.adjustedsurv.r:157:3', 'test_plot.adjustedsurv.r:163:3', 'test_plot.adjustedsurv.r:169:3', 'test_plot.adjustedsurv.r:175:3', 'test_plot.adjustedsurv.r:181:3', 'test_plot.adjustedsurv.r:192:3', 'test_plot.adjustedsurv.r:198:3', 'test_plot.adjustedsurv.r:204:3', 'test_plot.adjustedsurv.r:210:3', 'test_plot.adjustedsurv.r:216:3', 'test_plot.adjustedsurv.r:223:3', 'test_plot.adjustedsurv.r:256:3', 'test_plot.adjustedsurv.r:265:3', 'test_plot.adjustedsurv.r:271:3', 'test_plot.adjustedsurv.r:277:3', 'test_plot.adjustedsurv.r:284:3', 'test_plot.adjustedsurv.r:291:3', 'test_plot.adjustedsurv.r:298:3', 'test_plot.adjustedsurv.r:304:3', 'test_plot.adjustedsurv.r:310:3', 'test_plot.adjustedsurv.r:318:3', 'test_plot.adjustedsurv.r:327:3', 'test_plot.adjustedsurv.r:333:3', 'test_plot.adjustedsurv.r:340:3', 'test_plot.adjustedsurv.r:346:3', 'test_plot.adjustedsurv.r:354:3', 'test_plot.adjustedsurv.r:363:3', 'test_plot.adjustedsurv.r:370:3', 'test_plot.adjustedsurv.r:377:3', 'test_plot.adjustedsurv.r:387:3', 'test_plot.adjustedsurv.r:394:3', 'test_plot.adjustedsurv.r:401:3', 'test_plot.adjustedsurv.r:408:3', 'test_plot.adjustedsurv.r:435:3', 'test_plot.adjustedsurv.r:442:3', 'test_plot.adjustedsurv.r:449:3', 'test_plot.adjustedsurv.r:456:3', 'test_plot_auc_curve.r:22:3', 'test_plot_auc_curve.r:28:3', 'test_plot_auc_curve.r:34:3', 'test_plot_auc_curve.r:40:3', 'test_plot_auc_curve.r:46:3', 'test_plot_auc_curve.r:52:3', 'test_plot_auc_curve.r:59:3', 'test_plot_auc_curve.r:65:3', 'test_plot_auc_curve.r:71:3', 'test_plot_auc_curve.r:77:3', 'test_plot_auc_curve.r:84:3', 'test_plot_auc_curve.r:91:3', 'test_plot_auc_curve.r:97:3', 'test_plot_auc_curve.r:103:3', 'test_plot_auc_curve.r:109:3', 'test_plot_auc_curve.r:115:3', 'test_plot_auc_curve.r:121:3', 'test_plot_auc_curve.r:128:3', 'test_plot_auc_curve.r:134:3', 'test_plot_auc_curve.r:140:3', 'test_plot_auc_curve.r:146:3', 'test_plot_curve_diff.r:21:3', 'test_plot_curve_diff.r:27:3', 'test_plot_curve_diff.r:33:3', 'test_plot_curve_diff.r:39:3', 'test_plot_curve_diff.r:45:3', 'test_plot_curve_diff.r:51:3', 'test_plot_curve_diff.r:57:3', 'test_plot_curve_diff.r:63:3', 'test_plot_curve_diff.r:69:3', 'test_plot_curve_diff.r:75:3', 'test_plot_curve_diff.r:81:3', 'test_plot_curve_diff.r:88:3', 'test_plot_curve_diff.r:95:3', 'test_plot_curve_diff.r:101:3', 'test_plot_curve_diff.r:107:3', 'test_plot_curve_diff.r:113:3', 'test_plot_curve_diff.r:119:3', 'test_plot_curve_diff.r:129:3', 'test_plot_curve_diff.r:137:3', 'test_plot_curve_diff.r:143:3', 'test_plot_curve_diff.r:152:3', 'test_plot_curve_diff.r:169:3', 'test_plot_curve_ratio.r:21:3', 'test_plot_curve_ratio.r:27:3', 'test_plot_curve_ratio.r:33:3', 'test_plot_curve_ratio.r:39:3', 'test_plot_curve_ratio.r:45:3', 'test_plot_curve_ratio.r:51:3', 'test_plot_curve_ratio.r:57:3', 'test_plot_curve_ratio.r:74:3' [ FAIL 0 | WARN 4 | SKIP 170 | PASS 1688 ] > > proc.time() user system elapsed 209.37 13.75 247.45