Using the tidymodels package for survival analysis code errors

zhangkai · July 28, 2022, 1:15pm

My recent research needs to compare different machine learning survival analysis modeling methods. I used the tidymodels package on classification problems and felt very good. I found relevant tutorials on Google, and the website is as follows: Posts /2021/11/survival-analysis-parsnip-adjacent/.
I followed the code of the tutorial exactly, but there is still an error report, I don't know if it is a problem with the package itself. thanks for your answer

rm(list = ls()) 
options(stringsAsFactors = T)
#> Warning in options(stringsAsFactors = T): 'options(stringsAsFactors = TRUE)' is
#> deprecated and will be disabled

Sys.setenv(LANGUAGE = "en")
library(tidyverse)
#> Warning: package 'tidyverse' was built under R version 4.0.5
#> Warning: package 'ggplot2' was built under R version 4.0.5
#> Warning: package 'tidyr' was built under R version 4.0.5
#> Warning: package 'readr' was built under R version 4.0.5
#> Warning: package 'dplyr' was built under R version 4.0.5
#> Warning: package 'forcats' was built under R version 4.0.5
library(tidymodels)
#> Warning: package 'tidymodels' was built under R version 4.0.5
#> Registered S3 method overwritten by 'tune':
#>   method                   from   
#>   required_pkgs.model_spec parsnip
#> Warning: package 'broom' was built under R version 4.0.5
#> Warning: package 'dials' was built under R version 4.0.5
#> Warning: package 'infer' was built under R version 4.0.5
#> Warning: package 'modeldata' was built under R version 4.0.5
#> Warning: package 'recipes' was built under R version 4.0.5
#> Warning: package 'tune' was built under R version 4.0.5
#> Warning: package 'workflows' was built under R version 4.0.5
#> Warning: package 'workflowsets' was built under R version 4.0.5
#> Warning: package 'yardstick' was built under R version 4.0.5
library(censored)
#> Loading required package: survival
#> Warning: package 'survival' was built under R version 4.0.5
library(survival)

# 载入数据集

bladder_train <- bladder[-c(1:3),]
bladder_test <- bladder[1:3,]

cox_spec <- proportional_hazards(penalty = 0.123) %>%
  set_engine("glmnet")


f_fit <- fit(cox_spec,
             Surv(stop, event) ~ rx + size + number + strata(enum),
             data = bladder_train)
#> Error: 'stratifySurv' is not an exported object from 'namespace:glmnet'

f_pred <- predict(f_fit, new_data = bladder_test,
                  type = "survival", time = seq(0, 20, 1))
#> Error in predict(f_fit, new_data = bladder_test, type = "survival", time = seq(0, : object 'f_fit' not found

f_pred <- f_pred %>% 
  mutate(id = factor(1:3)) %>% 
  unnest(cols = .pred)
#> Error in mutate(., id = factor(1:3)): object 'f_pred' not found

f_pred %>% 
  ggplot(aes(x = .time, y = .pred_survival, col = id)) +
  geom_step()
#> Error in ggplot(., aes(x = .time, y = .pred_survival, col = id)): object 'f_pred' not found

mattwarkentin · July 29, 2022, 4:09pm

Hi @zhangkai,

I am unable to reproduce your issue. What version of censored and parsnip are you using? Can you try updating the censored package and try again?

library(tidyverse)
library(tidymodels)
library(censored)
#> Loading required package: survival
library(survival)

bladder_train <- bladder[-c(1:3),]
bladder_test <- bladder[1:3,]

cox_spec <- 
  proportional_hazards(penalty = 0.123) %>%
  set_engine("glmnet")


f_fit <- fit(cox_spec,
             Surv(stop, event) ~ rx + size + number + strata(enum),
             data = bladder_train)

f_pred <- predict(f_fit, new_data = bladder_test,
                  type = "survival", time = seq(0, 20, 1))

f_pred <- f_pred %>% 
  mutate(id = factor(1:3)) %>% 
  unnest(cols = .pred)

f_pred %>% 
  ggplot(aes(x = .time, y = .pred_survival, col = id)) +
  geom_step()

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value                       
#>  version  R version 4.0.5 (2021-03-31)
#>  os       macOS Big Sur 10.16         
#>  system   x86_64, darwin17.0          
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_CA.UTF-8                 
#>  ctype    en_CA.UTF-8                 
#>  tz       America/Toronto             
#>  date     2022-07-29                  
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
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#>  backports      1.4.1       2021-12-13 [1]
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#>  cellranger     1.1.0       2016-07-27 [1]
#>  censored     * 0.1.0       2022-06-22 [1]
#>  class          7.3-18      2021-01-24 [2]
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#>  Matrix         1.3-2       2021-01-06 [2]
#>  mime           0.12        2021-09-28 [1]
#>  modeldata    * 0.1.1       2021-07-14 [1]
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#>  tidymodels   * 0.2.0.9000  2022-05-05 [1]
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#>  yaml           2.3.5       2022-02-21 [1]
#>  yardstick    * 1.0.0.9000  2022-07-07 [1]
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#> [1] /Users/matt/Library/R/4.0/library
#> [2] /Library/Frameworks/R.framework/Versions/4.0/Resources/library

zhangkai · July 30, 2022, 2:03am

I updated the two packages you mentioned, but there is still a problem. The following is the version of the local program. I don't know if the problem lies in the glmnet package.

R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=Chinese (Simplified)_China.936
[2] LC_CTYPE=Chinese (Simplified)_China.936
[3] LC_MONETARY=Chinese (Simplified)_China.936
[4] LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_China.936

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] censored_0.1.0.9000 survival_3.3-1 yardstick_1.0.0
[4] workflowsets_1.0.0 workflows_1.0.0 tune_1.0.0
[7] rsample_1.0.0 recipes_1.0.1 parsnip_1.0.0
[10] modeldata_1.0.0 infer_1.0.2 dials_1.0.0
[13] scales_1.2.0 broom_1.0.0 tidymodels_1.0.0
[16] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9
[19] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0
[22] tibble_3.1.8 ggplot2_3.3.6 tidyverse_1.3.1

loaded via a namespace (and not attached):
[1] colorspace_2.0-3 ellipsis_0.3.2 class_7.3-17
[4] rprojroot_2.0.2 fs_1.5.2 rstudioapi_0.13
[7] listenv_0.8.0 furrr_0.2.3 remotes_2.4.2
[10] prodlim_2019.11.13 fansi_1.0.3 lubridate_1.8.0
[13] xml2_1.3.2 codetools_0.2-18 splines_4.0.3
[16] cachem_1.0.4 pkgload_1.2.4 jsonlite_1.7.2
[19] dbplyr_2.1.1 compiler_4.0.3 httr_1.4.2
[22] backports_1.4.1 assertthat_0.2.1 Matrix_1.2-18
[25] fastmap_1.1.0 cli_3.3.0 prettyunits_1.1.1
[28] tools_4.0.3 gtable_0.3.0 glue_1.6.2
[31] tinytex_0.40 Rcpp_1.0.7 cellranger_1.1.0
[34] DiceDesign_1.9 vctrs_0.4.1 iterators_1.0.13
[37] timeDate_3043.102 gower_0.2.2 xfun_0.29
[40] globals_0.15.1 ps_1.4.0 brio_1.1.0
[43] testthat_3.1.4 rvest_1.0.1 lifecycle_1.0.1
[46] devtools_2.4.3 future_1.21.0 MASS_7.3-53
[49] ipred_0.9-12 hms_1.1.1 parallel_4.0.3
[52] yaml_2.3.5 curl_4.3 memoise_2.0.1
[55] rpart_4.1-15 stringi_1.7.6 desc_1.4.1
[58] foreach_1.5.1 lhs_1.1.3 hardhat_1.2.0
[61] pkgbuild_1.3.1 shape_1.4.5 lava_1.6.8.1
[64] rlang_1.0.4 pkgconfig_2.0.3 lattice_0.20-41
[67] processx_3.5.2 tidyselect_1.1.2 parallelly_1.31.1
[70] magrittr_2.0.2 R6_2.5.1 generics_0.1.3
[73] DBI_1.1.0 pillar_1.8.0 haven_2.4.3
[76] withr_2.5.0 nnet_7.3-14 modelr_0.1.8
[79] crayon_1.5.0 utf8_1.2.2 tzdb_0.2.0
[82] usethis_2.1.5 grid_4.0.3 readxl_1.3.1
[85] callr_3.7.0 reprex_2.0.0 digest_0.6.29
[88] glmnet_4.0-2 munsell_0.5.0 GPfit_1.0-8
[91] sessioninfo_1.1.1

Max · July 30, 2022, 2:07pm

I'd update the glmnet package. It is currently at 4.1-4

zhangkai · July 31, 2022, 12:53am

Thank you very much for your answer, it was indeed a problem with the glmnet package, the above problem was solved after the update

system · August 7, 2022, 12:53am

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