Package check result: NOTE Check: CRAN incoming feasibility, Result: NOTE Maintainer: ‘Thomas A. Gerds ’ Version contains leading zeroes (2026.03.08) Changes to worse in reverse depends: Package: adjustedCurves Check: tests New result: ERROR Running ‘testthat.R’ [145s/161s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > 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 2026.02.13 > 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=2791488 on localhost:11183 at 01:22:31.745 starting worker pid=2791487 on localhost:11183 at 01:22:31.792 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 2026.02.13 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 2026.02.13 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=2792048 on localhost:11183 at 01:22:35.706 starting worker pid=2792047 on localhost:11183 at 01:22:35.734 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 2026.02.13 Attaching package: ‘riskRegression’ The following objects are masked from ‘package:pec’: ipcw, selectCox riskRegression version 2026.02.13 Loading required package: MASS Attaching package: ‘riskRegression’ The following objects are masked from ‘package:pec’: ipcw, selectCox ## ## 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: 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 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=2792610 on localhost:11183 at 01:22:40.201 starting worker pid=2792611 on localhost:11183 at 01:22:40.229 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 2026.02.13 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 2026.02.13 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=2793039 on localhost:11183 at 01:22:44.074 starting worker pid=2793040 on localhost:11183 at 01:22:44.106 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 Attaching package: ‘prodlim’ The following objects are masked from ‘package:eventglm’: leaveOneOut.competing.risks, leaveOneOut.survival Loading required package: prodlim Attaching package: ‘prodlim’ The following objects are masked from ‘package:eventglm’: leaveOneOut.competing.risks, leaveOneOut.survival riskRegression version 2026.02.13 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 2026.02.13 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: Ran out of iterations and did not converge 2: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Loglik converged before variable 1 ; coefficient may be infinite. 1: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : 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 ate_checkArgs(call = call, object.event = object.event, object.censor = object.censor, :In predict.CauseSpecificCox(object = object, newdata = newdata, : Rare event 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 16 | WARN 5 | SKIP 169 | PASS 1653 ] ══ 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' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_cif_direct.r:167:3'): riskRegression, 2 treatments, no boot ──── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:167:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:181:3'): riskRegression, 2 treatments, with boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:181:3 2. └─adjustedCurves:::adjustedcif_boot(...) 3. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::cif_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:196:3'): ARR, 2 treatments, no boot ─────────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:196:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:210:3'): ARR, 2 treatments, with boot ───────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:210:3 2. └─adjustedCurves:::adjustedcif_boot(...) 3. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::cif_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:438:3'): riskRegression, > 2 treatments, no boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:438:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:452:3'): riskRegression, > 2 treatments, with boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:452:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:466:3'): ARR, > 2 treatments, no boot ───────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:466:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_cif_direct.r:480:3'): ARR, > 2 treatments, with boot ─────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedcif(...) at test_cif_direct.r:480:3 2. ├─R.utils::doCall(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(cif_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::cif_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:204:3'): riskRegression, 2 treatments, no boot ─── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:204:3 2. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::surv_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:217:3'): riskRegression, 2 treatments, with boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:217:3 2. └─adjustedCurves:::adjustedsurv_boot(...) 3. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::surv_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:232:3'): ARR, 2 treatments, no boot ────────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:232:3 2. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::surv_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:245:3'): ARR, 2 treatments, with boot ──────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:245:3 2. └─adjustedCurves:::adjustedsurv_boot(...) 3. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::surv_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:390:3'): riskRegression, > 2 treatments, no boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:390:3 2. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::surv_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:403:3'): riskRegression, > 2 treatments, with boot ── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:403:3 2. └─adjustedCurves:::adjustedsurv_boot(...) 3. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::surv_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:418:3'): ARR, 2 treatments, no boot ────────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:418:3 2. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 3. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. │ └─base::do.call(.fcn, args = args, envir = envir) 5. └─adjustedCurves (local) ``(...) 6. └─adjustedCurves:::surv_g_comp(...) 7. ├─adjustedCurves:::quiet(...) 8. │ └─base::force(x) 9. ├─riskRegression::predictRisk(...) 10. └─riskRegression:::predictRisk.riskRegression(...) 11. ├─stats::predict(object, newdata = newdata, times = times) 12. └─riskRegression:::predict.riskRegression(...) 13. └─prodlim::EventHistory.frame(...) ── Error ('test_surv_direct.r:431:3'): ARR, 2 treatments, with boot ──────────── Error in `prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", "strata", "prop", "const", "tp"), stripSpecials = c("timevar", "prop"), stripArguments = list(prop = list(power = 0), timevar = list(test = 0)), stripAlias = list(timevar = c("strata"), prop = c("tp", "const")), stripUnspecials = "prop", specialsDesign = TRUE, dropIntercept = TRUE, check.formula = FALSE, response = FALSE)`: object 'is_event_history' not found Backtrace: ▆ 1. └─adjustedCurves::adjustedsurv(...) at test_surv_direct.r:431:3 2. └─adjustedCurves:::adjustedsurv_boot(...) 3. ├─R.utils::doCall(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 4. ├─R.utils::doCall.default(surv_fun, args = args, .ignoreUnusedArgs = FALSE) 5. │ └─base::do.call(.fcn, args = args, envir = envir) 6. └─adjustedCurves (local) ``(...) 7. └─adjustedCurves:::surv_g_comp(...) 8. ├─adjustedCurves:::quiet(...) 9. │ └─base::force(x) 10. ├─riskRegression::predictRisk(...) 11. └─riskRegression:::predictRisk.riskRegression(...) 12. ├─stats::predict(object, newdata = newdata, times = times) 13. └─riskRegression:::predict.riskRegression(...) 14. └─prodlim::EventHistory.frame(...) [ FAIL 16 | WARN 5 | SKIP 169 | PASS 1653 ] Error: ! Test failures. Execution halted Package: riskRegression Check: examples New result: ERROR Running examples in ‘riskRegression-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: plot.riskRegression > ### Title: Plotting predicted risk > ### Aliases: plot.riskRegression > ### Keywords: survival > > ### ** Examples > > > library(survival) > library(prodlim) > data(Melanoma) > fit.arr <- ARR(Hist(time,status)~invasion+age+strata(sex),data=Melanoma,cause=1) > plot(fit.arr,xlim=c(500,3000)) Error in prodlim::EventHistory.frame(formula(tt), newdata, specials = c("timevar", : object 'is_event_history' not found Calls: plot ... -> predict.riskRegression -> Execution halted