R Under development (unstable) (2026-02-04 r89376 ucrt) -- "Unsuffered Consequences" Copyright (C) 2026 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) > 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 4.10-15, Build Date: 2024-10-14) ## 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) > library(riskRegression) riskRegression version 2025.09.17 > 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 Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Loading required namespace: doParallel starting worker pid=52400 on localhost:11070 at 13:49:59.225 starting worker pid=97864 on localhost:11070 at 13:49:59.234 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 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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=15120 on localhost:11070 at 13:50:05.510 starting worker pid=44024 on localhost:11070 at 13:50:05.525 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 Loading required package: adjustedCurves loaded adjustedCurves and set parent environment 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 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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=30328 on localhost:11070 at 13:50:12.688 starting worker pid=23332 on localhost:11070 at 13:50:12.718 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: '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: 'prodlim' The following objects are masked from 'package:eventglm': leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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. ## riskRegression version 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS Attaching package: 'dplyr' 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 ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: rngtools Attaching package: 'dplyr' 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=105892 on localhost:11070 at 13:50:18.557 starting worker pid=91100 on localhost:11070 at 13:50:18.567 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 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 riskRegression version 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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 2025.09.17 Attaching package: 'riskRegression' The following objects are masked from 'package:pec': ipcw, selectCox Loading required package: MASS ## ## Matching (Version 4.10-15, Build Date: 2024-10-14) ## 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: 'dplyr' 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: 1: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :Warning messages: Loglik converged before variable 1 ; coefficient may be infinite. 1: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Ran out of iterations and did not converge 2: 2: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Loglik converged before variable 1 ; coefficient may be infinite. In ate_checkArgs(call = call, object.event = object.event, object.censor = object.censor, : Rare event 3: In ate_checkArgs(call = call, object.event = object.event, object.censor = object.censor, : Rare event 4: In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. 5: In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. 6: In predict.CauseSpecificCox(object = object, newdata = newdata, : Estimated risk outside the range [0,1]. Consider setting the argument 'product.limit' to FALSE. Loading required namespace: cowplot Loading required namespace: ggpp Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, supply an argument to `focal`. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. Assuming "Treatment" is the treated level. If not, recode the treatment so that 1 is treated and 0 is control. [ FAIL 0 | WARN 4 | SKIP 169 | PASS 1701 ] ══ Skipped tests (169) ═════════════════════════════════════════════════════════ • On CRAN (169): 'test_adjusted_curve_test.r:43:1', 'test_adjusted_curve_test.r:88:1', 'test_adjusted_curve_test.r:138:1', 'test_adjusted_curve_test.r:190:1', 'test_adjustedcif.method_S3.r:15:1', 'test_adjustedcif.method_S3.r:19:1', 'test_adjustedcif_S3.r:17:1', 'test_adjustedcif_S3.r:21:1', 'test_adjustedcif_S3.r:26:1', 'test_adjustedcif_S3.r:31:1', 'test_adjustedcif_S3.r:36:1', 'test_adjustedcif_S3.r:41:1', 'test_adjustedcif_S3.r:46:1', 'test_adjustedcif_S3.r:51:1', 'test_adjustedcif_S3.r:56:1', 'test_adjustedcif_S3.r:61:1', 'test_adjustedcif_S3.r:67:1', 'test_adjustedcif_S3.r:73:1', 'test_adjustedcif_S3.r:79:1', 'test_adjustedsurv.method_S3.r:14:1', 'test_adjustedsurv.method_S3.r:18:1', 'test_adjustedsurv_S3.r:16:1', 'test_adjustedsurv_S3.r:20:1', 'test_adjustedsurv_S3.r:25:1', 'test_adjustedsurv_S3.r:30:1', 'test_adjustedsurv_S3.r:35:1', 'test_adjustedsurv_S3.r:40:1', 'test_adjustedsurv_S3.r:45:1', 'test_adjustedsurv_S3.r:50:1', 'test_adjustedsurv_S3.r:55:1', 'test_adjustedsurv_S3.r:60:1', 'test_adjustedsurv_S3.r:65:1', 'test_adjustedsurv_S3.r:70:1', 'test_adjustedsurv_S3.r:75:1', 'test_adjustedsurv_S3.r:80:1', 'test_adjustedsurv_S3.r:85:1', 'test_adjustedsurv_S3.r:90:1', 'test_adjustedsurv_S3.r:95:1', 'test_adjustedsurv_S3.r:100:1', 'test_adjustedsurv_S3.r:106:1', 'test_adjustedsurv_S3.r:112:1', 'test_adjustedsurv_S3.r:118:1', 'test_curve_test_S3.r:20:1', 'test_curve_test_S3.r:24:1', 'test_plot.adjustedcif.r:19:1', 'test_plot.adjustedcif.r:25:1', 'test_plot.adjustedcif.r:31:1', 'test_plot.adjustedcif.r:37:1', 'test_plot.adjustedcif.r:43:1', 'test_plot.adjustedcif.r:54:1', 'test_plot.adjustedcif.r:65:1', 'test_plot.adjustedcif.r:81:1', 'test_plot.adjustedcif.r:97:1', 'test_plot.adjustedcif.r:103:1', 'test_plot.adjustedcif.r:109:1', 'test_plot.adjustedcif.r:115:1', 'test_plot.adjustedcif.r:121:1', 'test_plot.adjustedcif.r:128:1', 'test_plot.adjustedcif.r:134:1', 'test_plot.adjustedcif.r:140:1', 'test_plot.adjustedcif.r:151:1', 'test_plot.adjustedcif.r:157:1', 'test_plot.adjustedcif.r:163:1', 'test_plot.adjustedcif.r:169:1', 'test_plot.adjustedcif.r:176:1', 'test_plot.adjustedcif.r:182:1', 'test_plot.adjustedcif.r:188:1', 'test_plot.adjustedcif.r:195:1', 'test_plot.adjustedsurv.r:35:1', 'test_plot.adjustedsurv.r:41:1', 'test_plot.adjustedsurv.r:47:1', 'test_plot.adjustedsurv.r:53:1', 'test_plot.adjustedsurv.r:59:1', 'test_plot.adjustedsurv.r:70:1', 'test_plot.adjustedsurv.r:81:1', 'test_plot.adjustedsurv.r:97:1', 'test_plot.adjustedsurv.r:113:1', 'test_plot.adjustedsurv.r:123:1', 'test_plot.adjustedsurv.r:129:1', 'test_plot.adjustedsurv.r:135:1', 'test_plot.adjustedsurv.r:141:1', 'test_plot.adjustedsurv.r:147:1', 'test_plot.adjustedsurv.r:154:1', 'test_plot.adjustedsurv.r:160:1', 'test_plot.adjustedsurv.r:166:1', 'test_plot.adjustedsurv.r:172:1', 'test_plot.adjustedsurv.r:178:1', 'test_plot.adjustedsurv.r:189:1', 'test_plot.adjustedsurv.r:196:1', 'test_plot.adjustedsurv.r:202:1', 'test_plot.adjustedsurv.r:208:1', 'test_plot.adjustedsurv.r:215:1', 'test_plot.adjustedsurv.r:222:1', 'test_plot.adjustedsurv.r:230:1', 'test_plot.adjustedsurv.r:267:1', 'test_plot.adjustedsurv.r:273:1', 'test_plot.adjustedsurv.r:279:1', 'test_plot.adjustedsurv.r:286:1', 'test_plot.adjustedsurv.r:292:1', 'test_plot.adjustedsurv.r:299:1', 'test_plot.adjustedsurv.r:306:1', 'test_plot.adjustedsurv.r:312:1', 'test_plot.adjustedsurv.r:318:1', 'test_plot.adjustedsurv.r:326:1', 'test_plot.adjustedsurv.r:335:1', 'test_plot.adjustedsurv.r:341:1', 'test_plot.adjustedsurv.r:348:1', 'test_plot.adjustedsurv.r:354:1', 'test_plot.adjustedsurv.r:362:1', 'test_plot.adjustedsurv.r:371:1', 'test_plot.adjustedsurv.r:378:1', 'test_plot.adjustedsurv.r:389:1', 'test_plot.adjustedsurv.r:395:1', 'test_plot.adjustedsurv.r:402:1', 'test_plot.adjustedsurv.r:410:1', 'test_plot.adjustedsurv.r:436:1', 'test_plot.adjustedsurv.r:443:1', 'test_plot.adjustedsurv.r:450:1', 'test_plot.adjustedsurv.r:457:1', 'test_plot_auc_curve.r:19:1', 'test_plot_auc_curve.r:25:1', 'test_plot_auc_curve.r:31:1', 'test_plot_auc_curve.r:37:1', 'test_plot_auc_curve.r:43:1', 'test_plot_auc_curve.r:49:1', 'test_plot_auc_curve.r:56:1', 'test_plot_auc_curve.r:62:1', 'test_plot_auc_curve.r:68:1', 'test_plot_auc_curve.r:74:1', 'test_plot_auc_curve.r:80:1', 'test_plot_auc_curve.r:87:1', 'test_plot_auc_curve.r:94:1', 'test_plot_auc_curve.r:100:1', 'test_plot_auc_curve.r:106:1', 'test_plot_auc_curve.r:112:1', 'test_plot_auc_curve.r:119:1', 'test_plot_auc_curve.r:125:1', 'test_plot_auc_curve.r:131:1', 'test_plot_auc_curve.r:137:1', 'test_plot_curve_diff.r:18:1', 'test_plot_curve_diff.r:24:1', 'test_plot_curve_diff.r:30:1', 'test_plot_curve_diff.r:38:1', 'test_plot_curve_diff.r:44:1', 'test_plot_curve_diff.r:50:1', 'test_plot_curve_diff.r:58:1', 'test_plot_curve_diff.r:64:1', 'test_plot_curve_diff.r:70:1', 'test_plot_curve_diff.r:76:1', 'test_plot_curve_diff.r:82:1', 'test_plot_curve_diff.r:88:1', 'test_plot_curve_diff.r:95:1', 'test_plot_curve_diff.r:102:1', 'test_plot_curve_diff.r:108:1', 'test_plot_curve_diff.r:114:1', 'test_plot_curve_diff.r:120:1', 'test_plot_curve_diff.r:126:1', 'test_plot_curve_diff.r:138:1', 'test_plot_curve_diff.r:144:1', 'test_plot_curve_diff.r:150:1', 'test_plot_curve_diff.r:172:1', 'test_plot_curve_ratio.r:18:1', 'test_plot_curve_ratio.r:24:1', 'test_plot_curve_ratio.r:30:1', 'test_plot_curve_ratio.r:36:1', 'test_plot_curve_ratio.r:42:1', 'test_plot_curve_ratio.r:48:1', 'test_plot_curve_ratio.r:54:1', 'test_plot_curve_ratio.r:71:1' [ FAIL 0 | WARN 4 | SKIP 169 | PASS 1701 ] > > proc.time() user system elapsed 237.96 11.78 276.54