Last updated on 2026-10-22 23:57:00 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.2.0 | 6.28 | 138.57 | 144.85 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.2.0 | 5.16 | 102.14 | 107.30 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.2.0 | 98.08 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.2.0 | 5.00 | 95.17 | 100.17 | ERROR | |
| r-devel-windows-x86_64 | 0.2.0 | 10.00 | 146.00 | 156.00 | OK | |
| r-patched-linux-x86_64 | 0.2.0 | 6.84 | 131.77 | 138.61 | OK | |
| r-release-linux-x86_64 | 0.2.0 | 7.27 | 130.71 | 137.98 | OK | |
| r-release-macos-arm64 | 0.2.0 | 2.00 | 38.00 | 40.00 | OK | |
| r-release-macos-x86_64 | 0.2.0 | 5.00 | 141.00 | 146.00 | OK | |
| r-release-windows-x86_64 | 0.2.0 | 9.00 | 136.00 | 145.00 | OK | |
| r-oldrel-macos-arm64 | 0.2.0 | 2.00 | 40.00 | 42.00 | OK | |
| r-oldrel-macos-x86_64 | 0.2.0 | 5.00 | 121.00 | 126.00 | OK | |
| r-oldrel-windows-x86_64 | 0.2.0 | 12.00 | 197.00 | 209.00 | OK |
Version: 0.2.0
Check: examples
Result: ERROR
Running examples in ‘triageR-Ex.R’ failed
The error most likely occurred in:
> ### Name: tr_validate_survival
> ### Title: Validate a clinical survival model
> ### Aliases: tr_validate_survival
>
> ### ** Examples
>
> if (requireNamespace("survival", quietly = TRUE)) {
+ library(survival)
+ lung_clean <- lung
+ lung_clean$status <- lung_clean$status - 1
+ lung_clean <- lung_clean[stats::complete.cases(lung_clean), ]
+ model <- tr_fit_survival(lung_clean, time_col = "time",
+ event_col = "status", engine = "cox_ph")
+ tr_validate_survival(model, newdata = lung_clean)
+ }
Survival model fitted successfully using engine: cox_ph
Error in a$specials[[i]] : subscript out of bounds
Calls: tr_validate_survival ... <Anonymous> -> get_missings_coxph -> <Anonymous> -> off
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.2.0
Check: tests
Result: ERROR
Running ‘spelling.R’
Running ‘testthat.R’ [14s/17s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(triageR)
>
> test_check("triageR")
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[low_epv]
Low events-per-variable ratio (EPV = 8). Clinical prediction modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more data.
[small_sample]
Sample size is small (n = 60). Results should be interpreted cautiously and external validation is strongly recommended.
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[zero_variance]
Predictor 'constant_col' has zero variance (same value for all patients) and contributes nothing to the model.
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[low_epv]
Low events-per-variable ratio (EPV = 4.3). Clinical prediction modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more data.
[small_sample]
Sample size is small (n = 50). Results should be interpreted cautiously and external validation is strongly recommended.
Survival model fitted successfully using engine: cox_ph
--- triageR Pipeline Review ---
[low_event_rate]
Low event rate detected: only 6.7% of patients experienced the event (2 of 30). Heavy censoring can reduce statistical power and inflate variance in risk estimates.
[low_epv]
Low events-per-variable ratio (EPV = 2, based on 2 events). Survival modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more follow-up data.
[small_sample]
Sample size is small (n = 30). Results should be interpreted cautiously and external validation is strongly recommended.
Survival model fitted successfully using engine: cox_ph
--- triageR Pipeline Review ---
No major issues flagged.
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Missing data summary:
- 2 of 3 columns have missing values
- 4 total rows
# A tibble: 3 x 3
column n_missing pct_missing
<chr> <int> <dbl>
1 c 3 75
2 a 2 50
3 b 0 0
Missing data summary:
- 0 of 2 columns have missing values
- 3 total rows
# A tibble: 2 x 3
column n_missing pct_missing
<chr> <int> <dbl>
1 a 0 0
2 b 0 0
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Survival model fitted successfully using engine: cox_ph
Survival model fitted successfully using engine: survival_rf
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: random_forest
Survival model fitted successfully using engine: cox_ph
Saving _problems/test-model-validate-survival-8.R
Survival model fitted successfully using engine: cox_ph
Saving _problems/test-model-validate-survival-21.R
Model fitted successfully using engine: logistic_reg
Validation metrics (newdata):
# A tibble: 5 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 roc_auc binary 0.574
2 sens binary 0.176
3 spec binary 0.848
4 accuracy binary 0.62
5 brier_score binary 0.234
Confusion Matrix:
Truth
Prediction 0 1
0 28 14
1 5 3
Model fitted successfully using engine: logistic_reg
Validation metrics (training_data):
# A tibble: 5 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 roc_auc binary 0.658
2 sens binary 0.553
3 spec binary 0.679
4 accuracy binary 0.62
5 brier_score binary 0.232
Confusion Matrix:
Truth
Prediction 0 1
0 36 21
1 17 26
[ FAIL 2 | WARN 0 | SKIP 2 | PASS 70 ]
══ Skipped tests (2) ═══════════════════════════════════════════════════════════
• No GEMINI_API_KEY set - skipping live API test (1):
'test-agent-recommend.R:7:3'
• On CRAN (1): 'test-report-tripod.R:2:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-model-validate-survival.R:8:3'): tr_validate_survival computes a C-index for Cox PH ──
<subscriptOutOfBoundsError/error/condition>
Error in `a$specials[[i]]`: subscript out of bounds
Backtrace:
▆
1. ├─base::suppressWarnings(tr_validate_survival(model, newdata = df)) at test-model-validate-survival.R:8:3
2. │ └─base::withCallingHandlers(...)
3. ├─triageR::tr_validate_survival(model, newdata = df)
4. │ ├─stats::predict(model$workflow, new_data = newdata, type = "time")
5. │ └─workflows:::predict.workflow(...)
6. │ ├─stats::predict(fit, new_data, type = type, opts = opts, ...)
7. │ └─parsnip::predict.model_fit(...)
8. │ ├─parsnip::predict_time(object = object, new_data = new_data, ...)
9. │ └─parsnip::predict_time.model_fit(...)
10. │ └─rlang::eval_tidy(pred_call)
11. └─censored::survival_time_coxph(object = object, new_data = new_data)
12. └─censored:::get_missings_coxph(object$fit, new_data)
13. └─stats::delete.response(trms)
14. └─stats (local) off(a$specials[[i]])
── Error ('test-model-validate-survival.R:21:3'): tr_validate_survival warns when no newdata supplied ──
<subscriptOutOfBoundsError/error/condition>
Error in `a$specials[[i]]`: subscript out of bounds
Backtrace:
▆
1. ├─testthat::expect_warning(tr_validate_survival(model), "training data") at test-model-validate-survival.R:21:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─triageR::tr_validate_survival(model)
8. │ ├─stats::predict(model$workflow, new_data = newdata, type = "time")
9. │ └─workflows:::predict.workflow(...)
10. │ ├─stats::predict(fit, new_data, type = type, opts = opts, ...)
11. │ └─parsnip::predict.model_fit(...)
12. │ ├─parsnip::predict_time(object = object, new_data = new_data, ...)
13. │ └─parsnip::predict_time.model_fit(...)
14. │ └─rlang::eval_tidy(pred_call)
15. └─censored::survival_time_coxph(object = object, new_data = new_data)
16. └─censored:::get_missings_coxph(object$fit, new_data)
17. └─stats::delete.response(trms)
18. └─stats (local) off(a$specials[[i]])
[ FAIL 2 | WARN 0 | SKIP 2 | PASS 70 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.2.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘triageR-breast-cancer.Rmd’ using rmarkdown
[WARNING] Deprecated: --mathjax. Use --math-method=mathjax[:URL] instead.
--- finished re-building ‘triageR-breast-cancer.Rmd’
--- re-building ‘triageR-intro.Rmd’ using rmarkdown
[WARNING] Deprecated: --mathjax. Use --math-method=mathjax[:URL] instead.
--- finished re-building ‘triageR-intro.Rmd’
--- re-building ‘triageR-survival-analysis.Rmd’ using rmarkdown
Quitting from triageR-survival-analysis.Rmd:91-93 [unnamed-chunk-5]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `a$specials[[i]]`:
! subscript out of bounds
---
Backtrace:
▆
1. ├─triageR::tr_validate_survival(model_cox, newdata = lung_clean)
2. │ ├─stats::predict(model$workflow, new_data = newdata, type = "time")
3. │ └─workflows:::predict.workflow(...)
4. │ ├─stats::predict(fit, new_data, type = type, opts = opts, ...)
5. │ └─parsnip::predict.model_fit(...)
6. │ ├─parsnip::predict_time(object = object, new_data = new_data, ...)
7. │ └─parsnip::predict_time.model_fit(...)
8. │ └─rlang::eval_tidy(pred_call)
9. └─censored::survival_time_coxph(object = object, new_data = new_data)
10. └─censored:::get_missings_coxph(object$fit, new_data)
11. └─stats::delete.response(trms)
12. └─stats (local) off(a$specials[[i]])
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'triageR-survival-analysis.Rmd' failed with diagnostics:
subscript out of bounds
--- failed re-building ‘triageR-survival-analysis.Rmd’
SUMMARY: processing the following file failed:
‘triageR-survival-analysis.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.2.0
Check: tests
Result: ERROR
Running ‘spelling.R’
Running ‘testthat.R’ [15s/27s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(triageR)
>
> test_check("triageR")
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[low_epv]
Low events-per-variable ratio (EPV = 8). Clinical prediction modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more data.
[small_sample]
Sample size is small (n = 60). Results should be interpreted cautiously and external validation is strongly recommended.
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[zero_variance]
Predictor 'constant_col' has zero variance (same value for all patients) and contributes nothing to the model.
Model fitted successfully using engine: logistic_reg
--- triageR Pipeline Review ---
[low_epv]
Low events-per-variable ratio (EPV = 4.3). Clinical prediction modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more data.
[small_sample]
Sample size is small (n = 50). Results should be interpreted cautiously and external validation is strongly recommended.
Survival model fitted successfully using engine: cox_ph
--- triageR Pipeline Review ---
[low_event_rate]
Low event rate detected: only 6.7% of patients experienced the event (2 of 30). Heavy censoring can reduce statistical power and inflate variance in risk estimates.
[low_epv]
Low events-per-variable ratio (EPV = 2, based on 2 events). Survival modelling guidance generally recommends at least 10 events per predictor to avoid overfitting. Consider reducing predictors or collecting more follow-up data.
[small_sample]
Sample size is small (n = 30). Results should be interpreted cautiously and external validation is strongly recommended.
Survival model fitted successfully using engine: cox_ph
--- triageR Pipeline Review ---
No major issues flagged.
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Missing data summary:
- 2 of 3 columns have missing values
- 4 total rows
# A tibble: 3 x 3
column n_missing pct_missing
<chr> <int> <dbl>
1 c 3 75
2 a 2 50
3 b 0 0
Missing data summary:
- 0 of 2 columns have missing values
- 3 total rows
# A tibble: 2 x 3
column n_missing pct_missing
<chr> <int> <dbl>
1 a 0 0
2 b 0 0
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: logistic_reg
Survival model fitted successfully using engine: cox_ph
Survival model fitted successfully using engine: survival_rf
Model fitted successfully using engine: logistic_reg
Model fitted successfully using engine: random_forest
Survival model fitted successfully using engine: cox_ph
Saving _problems/test-model-validate-survival-8.R
Survival model fitted successfully using engine: cox_ph
Saving _problems/test-model-validate-survival-21.R
Model fitted successfully using engine: logistic_reg
Validation metrics (newdata):
# A tibble: 5 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 roc_auc binary 0.574
2 sens binary 0.176
3 spec binary 0.848
4 accuracy binary 0.62
5 brier_score binary 0.234
Confusion Matrix:
Truth
Prediction 0 1
0 28 14
1 5 3
Model fitted successfully using engine: logistic_reg
Validation metrics (training_data):
# A tibble: 5 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 roc_auc binary 0.658
2 sens binary 0.553
3 spec binary 0.679
4 accuracy binary 0.62
5 brier_score binary 0.232
Confusion Matrix:
Truth
Prediction 0 1
0 36 21
1 17 26
[ FAIL 2 | WARN 0 | SKIP 2 | PASS 70 ]
══ Skipped tests (2) ═══════════════════════════════════════════════════════════
• No GEMINI_API_KEY set - skipping live API test (1):
'test-agent-recommend.R:7:3'
• On CRAN (1): 'test-report-tripod.R:2:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-model-validate-survival.R:8:3'): tr_validate_survival computes a C-index for Cox PH ──
<subscriptOutOfBoundsError/error/condition>
Error in `a$specials[[i]]`: subscript out of bounds
Backtrace:
▆
1. ├─base::suppressWarnings(tr_validate_survival(model, newdata = df)) at test-model-validate-survival.R:8:3
2. │ └─base::withCallingHandlers(...)
3. ├─triageR::tr_validate_survival(model, newdata = df)
4. │ ├─stats::predict(model$workflow, new_data = newdata, type = "time")
5. │ └─workflows:::predict.workflow(...)
6. │ ├─stats::predict(fit, new_data, type = type, opts = opts, ...)
7. │ └─parsnip::predict.model_fit(...)
8. │ ├─parsnip::predict_time(object = object, new_data = new_data, ...)
9. │ └─parsnip::predict_time.model_fit(...)
10. │ └─rlang::eval_tidy(pred_call)
11. └─censored::survival_time_coxph(object = object, new_data = new_data)
12. └─censored:::get_missings_coxph(object$fit, new_data)
13. └─stats::delete.response(trms)
14. └─stats (local) off(a$specials[[i]])
── Error ('test-model-validate-survival.R:21:3'): tr_validate_survival warns when no newdata supplied ──
<subscriptOutOfBoundsError/error/condition>
Error in `a$specials[[i]]`: subscript out of bounds
Backtrace:
▆
1. ├─testthat::expect_warning(tr_validate_survival(model), "training data") at test-model-validate-survival.R:21:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─triageR::tr_validate_survival(model)
8. │ ├─stats::predict(model$workflow, new_data = newdata, type = "time")
9. │ └─workflows:::predict.workflow(...)
10. │ ├─stats::predict(fit, new_data, type = type, opts = opts, ...)
11. │ └─parsnip::predict.model_fit(...)
12. │ ├─parsnip::predict_time(object = object, new_data = new_data, ...)
13. │ └─parsnip::predict_time.model_fit(...)
14. │ └─rlang::eval_tidy(pred_call)
15. └─censored::survival_time_coxph(object = object, new_data = new_data)
16. └─censored:::get_missings_coxph(object$fit, new_data)
17. └─stats::delete.response(trms)
18. └─stats (local) off(a$specials[[i]])
[ FAIL 2 | WARN 0 | SKIP 2 | PASS 70 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc