• using R Under development (unstable) (2026-07-09 r90225)
• using platform: x86_64-pc-linux-gnu
• R was compiled by     gcc-16 (Debian 16.1.0-2) 16.1.0     GNU Fortran (Debian 16.1.0-2) 16.1.0
• running under: Debian GNU/Linux forky/sid
• using session charset: UTF-8 * current time: 2026-07-10 15:31:33 UTC
• checking for file ‘jointCompRisk/DESCRIPTION’ ... OK
• checking extension type ... Package
• this is package ‘jointCompRisk’ version ‘0.1.1’
• package encoding: UTF-8
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• checking whether package ‘jointCompRisk’ can be installed ... OK See the install log for details.
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• checking tests ... [3s/4s] ERROR   Running ‘testthat.R’ [3s/3s] Running the tests in ‘tests/testthat.R’ failed. Complete output:   > library(testthat)   > library(jointCompRisk)   >   > test_check("jointCompRisk")   Saving _problems/test-basic-32.R   [ FAIL 1 | WARN 0 | SKIP 0 | PASS 10 ]      ══ Failed tests ════════════════════════════════════════════════════════════════   ── Error ('test-basic.R:32:3'): do_cif_analysis returns formatted summaries ────   Error in `survfit.formula(Surv(etime, estatus) ~ 1, etype = etype2, data = data.w)`: the etype argument is no longer supported, use a factor as the status variable   Backtrace:       ▆    1. └─jointCompRisk::do_cif_analysis(prepped, tau = 15) at test-basic.R:32:3    2. └─jointCompRisk:::table1_cif(Treatment, Control, tau, 0, 1, 0)    3. └─jointCompRisk:::auc.var.joint(data1, tau, a, b, c)    4. ├─survival::survfit(Surv(etime, estatus) ~ 1, etype = etype2, data = data.w)    5. └─survival::survfit.formula(...)      [ FAIL 1 | WARN 0 | SKIP 0 | PASS 10 ]   Error:   ! Test failures.   Execution halted
• checking for unstated dependencies in vignettes ... OK
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[5s/6s] ERROR Error(s) in re-building vignettes:   ... --- re-building ‘Example_analysis.Rmd’ using rmarkdown Quitting from Example_analysis.Rmd:24-42 [unnamed-chunk-2] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <error/rlang_error> Error in `survfit.formula()`: ! the etype argument is no longer supported, use a factor as the status variable --- Backtrace:     ▆  1. └─jointCompRisk::do_cif_analysis(mydata_std, tau = 15)  2. └─jointCompRisk:::table1_cif(Treatment, Control, tau, 0, 1, 0)  3. └─jointCompRisk:::auc.var.joint(data1, tau, a, b, c)  4. ├─survival::survfit(Surv(etime, estatus) ~ 1, etype = etype2, data = data.w)  5. └─survival::survfit.formula(...) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error: processing vignette 'Example_analysis.Rmd' failed with diagnostics: the etype argument is no longer supported, use a factor as the status variable --- failed re-building ‘Example_analysis.Rmd’ --- re-building ‘Vignette.Rmd’ using rmarkdown main_df package:jointCompRisk R Documentation _ M_ a_ i_ n _ C_ o_ m_ p_ e_ t_ i_ n_ g _ R_ i_ s_ k_ s _ D_ a_ t_ a_ s_ e_ t _ S_ i_ m_ u_ l_ a_ t_ e_ d _ c_ l_ i_ n_ i_ c_ a_ l _ t_ r_ i_ a_ l _ d_ a_ t_ a _ w_ i_ t_ h _ c_ o_ m_ p_ e_ t_ i_ n_ g _ r_ i_ s_ k_ s _ s_ u_ r_ v_ i_ v_ a_ l _ o_ u_ t_ c_ o_ m_ e_ s. _ T_ h_ i_ s _ d_ a_ t_ a_ s_ e_ t _ f_ o_ l_ l_ o_ w_ s _ t_ h_ e _ s_ t_ r_ u_ c_ t_ u_ r_ e _ o_ f _ A_ d_ a_ p_ t_ i_ v_ e _ C_ O_ V_ I_ D-_ 1_ 9 _ T_ r_ e_ a_ t_ m_ e_ n_ t _ T_ r_ i_ a_ l_ s (_ A_ C_ T_ T) _ w_ i_ t_ h _ b_ u_ i_ l_ t-_ i_ n _ t_ r_ e_ a_ t_ m_ e_ n_ t _ e_ f_ f_ e_ c_ t_ s _ f_ o_ r _ d_ e_ m_ o_ n_ s_ t_ r_ a_ t_ i_ o_ n _ p_ u_ r_ p_ o_ s_ e_ s. _ D_ e_ s_ c_ r_ i_ p_ t_ i_ o_ n:      Main Competing Risks Dataset Simulated clinical trial data with      competing risks survival outcomes. This dataset follows the      structure of Adaptive COVID-19 Treatment Trials (ACTT) with      built-in treatment effects for demonstration purposes. _ U_ s_ a_ g_ e:      data(main_df)       _ F_ o_ r_ m_ a_ t:      A data frame with 150 rows and 7 variables:      ID           Patient identifier (character)      TimeToRecovery           Time to recovery event in days (numeric)      TimeToDeath           Time to death event in days (numeric)      RecoveryCensoringIndicator           Recovery censoring indicator (0=event observed, 1=censored)      DeathCensoringIndicator           Death censoring indicator (0=event observed, 1=censored)      BaselineScore           Baseline severity score, range 4-7 (numeric)      Treatment           Treatment arm indicator (0=control, 1=treatment) _ D_ e_ t_ a_ i_ l_ s:      This is a simulated dataset created for demonstration purposes      with realistic treatment effects built in: treatment group has      1.5× faster recovery times and 1.8× improved survival compared to      control. The data represents a clinical trial with competing risks      where patients can either recover or die, with administrative      censoring at 30 days. _ S_ o_ u_ r_ c_ e:      Simulated data based on Weibull distributions with      treatment-specific parameters _ E_ x_ a_ m_ p_ l_ e_ s:      data(main_df)      head(main_df)      summary(main_df)      # Compare outcomes by treatment      tapply(main_df$TimeToRecovery, main_df$Treatment, summary)      tapply(main_df$TimeToDeath, main_df$Treatment, summary)       long_df package:jointCompRisk R Documentation _ L_ o_ n_ g_ i_ t_ u_ d_ i_ n_ a_ l _ S_ e_ v_ e_ r_ i_ t_ y _ S_ c_ o_ r_ e_ s _ D_ a_ t_ a_ s_ e_ t _ D_ e_ s_ c_ r_ i_ p_ t_ i_ o_ n:      Repeated measurements of ordinal severity scores over time for the      same patients in the main_df dataset, with treatment-specific      trajectory patterns. _ U_ s_ a_ g_ e:      data(long_df)       _ F_ o_ r_ m_ a_ t:      A data frame with variable rows per patient:      PersonID           Patient identifier matching ID in main_df (character)      OrdinalScore           Severity score on 1-8 scale (numeric)      RelativeDay           Study day (numeric) starting from day 0 (baseline) _ D_ e_ t_ a_ i_ l_ s:      Measurements are taken at scheduled visits: days 0 (baseline), 1,      3, 5, 7, 10, 14, 18, 21, 25, 28. The trajectory follows      treatment-specific probabilities: treatment patients have 45 and      15 worsening probability, creating realistic differential clinical      progression patterns. _ S_ o_ u_ r_ c_ e:      Simulated data using treatment-specific random walk with      boundaries _ E_ x_ a_ m_ p_ l_ e_ s:      data(long_df)      data(main_df)      head(long_df)      # See data for first patient      subset(long_df, PersonID == "Patient_001")      # Compare average scores by treatment      long_df %>%        dplyr::left_join(main_df[,c("ID","Treatment")], by=c("PersonID"="ID")) %>%        dplyr::group_by(Treatment) %>%        dplyr::summarise(mean_score = mean(OrdinalScore))       Quitting from Vignette.Rmd:159-169 [unnamed-chunk-4] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <error/rlang_error> Error in `survfit.formula()`: ! the etype argument is no longer supported, use a factor as the status variable --- Backtrace:     ▆  1. └─jointCompRisk::do_cif_analysis(mydata_std, tau = 15)  2. └─jointCompRisk:::table1_cif(Treatment, Control, tau, 0, 1, 0)  3. └─jointCompRisk:::auc.var.joint(data1, tau, a, b, c)  4. ├─survival::survfit(Surv(etime, estatus) ~ 1, etype = etype2, data = data.w)  5. └─survival::survfit.formula(...) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Error: processing vignette 'Vignette.Rmd' failed with diagnostics: the etype argument is no longer supported, use a factor as the status variable --- failed re-building ‘Vignette.Rmd’ SUMMARY: processing the following files failed:   ‘Example_analysis.Rmd’ ‘Vignette.Rmd’ Error: Vignette re-building failed. Execution halted
• checking PDF version of manual ... [4s/5s] OK
• checking HTML version of manual ... [0s/1s] OK
• checking for non-standard things in the check directory ... OK
• DONE

Status: 2 ERRORs