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