Closed jalavery closed 7 months ago
Experimental support has been added to PR #243
Please note that you need to indicate exponentiate = TRUE
Fantastic, thank you for such a quick update @larmarange!
I re-ran the test example, and it looks like even with exponentiate = TRUE, the values displayed on the table are the un-exponentiated values. Would you mind please looking into this whenever you have a chance? Thank you!
library(survival)
#> Warning: package 'survival' was built under R version 4.1.3
library(gtsummary)
#> Warning: package 'gtsummary' was built under R version 4.1.3
# case-cohort model using the survival::cch function
# example from survival::cch()
## The complete Wilms Tumor Data
## (Breslow and Chatterjee, Applied Statistics, 1999)
## subcohort selected by simple random sampling.
##
subcoh <- nwtco$in.subcohort
selccoh <- with(nwtco, rel==1|subcoh==1)
ccoh.data <- nwtco[selccoh,]
ccoh.data$subcohort <- subcoh[selccoh]
## central-lab histology
ccoh.data$histol <- factor(ccoh.data$histol,labels=c("FH","UH"))
## tumour stage
ccoh.data$stage <- factor(ccoh.data$stage,labels=c("I","II","III","IV"))
ccoh.data$age <- ccoh.data$age/12 # Age in years
##
## Standard case-cohort analysis: simple random subcohort
##
fit.ccP <- cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data,
subcoh = ~subcohort, id=~seqno, cohort.size=4028)
summary(fit.ccP)
#> Case-cohort analysis,x$method, Prentice
#> with subcohort of 668 from cohort of 4028
#>
#> Call: cch(formula = Surv(edrel, rel) ~ stage + histol + age, data = ccoh.data,
#> subcoh = ~subcohort, id = ~seqno, cohort.size = 4028)
#>
#> Coefficients:
#> Coef HR (95% CI) p
#> stageII 0.735 2.085 1.498 2.900 0.000
#> stageIII 0.597 1.817 1.293 2.552 0.001
#> stageIV 1.384 3.991 2.672 5.963 0.000
#> histolUH 1.498 4.473 3.271 6.117 0.000
#> age 0.043 1.044 0.997 1.094 0.068
# tidy model output: success
broom::tidy(fit.ccP)
#> # A tibble: 5 x 7
#> term estimate std.error statistic p.value conf.low conf.high
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 stageII 0.735 0.168 4.36 1.30e- 5 0.404 1.06
#> 2 stageIII 0.597 0.173 3.44 5.77e- 4 0.257 0.937
#> 3 stageIV 1.38 0.205 6.76 1.40e-11 0.983 1.79
#> 4 histolUH 1.50 0.160 9.38 0 1.19 1.81
#> 5 age 0.0433 0.0237 1.82 6.83e- 2 -0.00324 0.0898
# this now runs
broom.helpers::tidy_plus_plus(fit.ccP, exponentiate = TRUE) %>%
select(term, label, estimate)
#> # A tibble: 7 x 3
#> term label estimate
#> <chr> <chr> <dbl>
#> 1 stageI I 1
#> 2 stageII II 0.735
#> 3 stageIII III 0.597
#> 4 stageIV IV 1.38
#> 5 histolFH FH 1
#> 6 histolUH UH 1.50
#> 7 age age 0.0433
# however, the log(HR) is being displayed as the HR, and the exponentiation seems to not be working
# HR for stage II should be exp(0.74) = 2.08 based on summary(fit.ccP)
# gtsummary::tbl_regression(fit.ccP, exponentiate = TRUE)
Created on 2024-01-24 with reprex v2.0.2
Sorry. There was an error in the implementation. Could you check the last version. Now exponentiate is optionnal.
Success! Thank you very much.
Is it possible to add support for a
survival::cch
model?Please see below for an example model and attempt to tidy it:
Created on 2024-01-23 with reprex v2.0.2
Session info
``` r sessioninfo::session_info() #> - Session info --------------------------------------------------------------- #> setting value #> version R version 4.1.2 (2021-11-01) #> os Windows 10 x64 (build 19045) #> system x86_64, mingw32 #> ui RTerm #> language (EN) #> collate English_United States.1252 #> ctype English_United States.1252 #> tz America/New_York #> date 2024-01-23 #> pandoc 3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown) #> #> - Packages ------------------------------------------------------------------- #> package * version date (UTC) lib source #> backports 1.4.1 2021-12-13 [1] CRAN (R 4.1.2) #> bayestestR 0.13.0 2022-09-18 [1] CRAN (R 4.1.3) #> broom 1.0.3 2023-01-25 [1] CRAN (R 4.1.3) #> broom.helpers 1.12.0 2023-02-09 [1] CRAN (R 4.1.3) #> cli 3.4.1 2022-09-23 [1] CRAN (R 4.1.3) #> coda 0.19-4 2020-09-30 [1] CRAN (R 4.0.3) #> codetools 0.2-18 2020-11-04 [1] CRAN (R 4.1.2) #> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.1.3) #> datawizard 0.6.4 2022-11-19 [1] CRAN (R 4.1.3) #> digest 0.6.30 2022-10-18 [1] CRAN (R 4.1.3) #> dplyr 1.1.0 2023-01-29 [1] CRAN (R 4.1.3) #> effectsize 0.8.2 2022-10-31 [1] CRAN (R 4.1.3) #> ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.0.5) #> emmeans 1.8.2 2022-10-27 [1] CRAN (R 4.1.3) #> estimability 1.4.1 2022-08-05 [1] CRAN (R 4.1.3) #> evaluate 0.20 2023-01-17 [1] CRAN (R 4.1.3) #> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.1.3) #> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.0.5) #> forcats 1.0.0 2023-01-29 [1] CRAN (R 4.1.3) #> fs 1.5.2 2021-12-08 [1] CRAN (R 4.1.3) #> generics 0.1.3 2022-07-05 [1] CRAN (R 4.1.3) #> ggplot2 3.4.1 2023-02-10 [1] CRAN (R 4.1.3) #> glue 1.6.2 2022-02-24 [1] CRAN (R 4.1.2) #> gt 0.8.0 2022-11-16 [1] CRAN (R 4.1.3) #> gtable 0.3.1 2022-09-01 [1] CRAN (R 4.1.3) #> gtsummary * 1.7.0 2023-01-13 [1] CRAN (R 4.1.3) #> haven 2.5.2 2023-02-28 [1] CRAN (R 4.1.3) #> hms 1.1.2 2022-08-19 [1] CRAN (R 4.1.3) #> htmltools 0.5.3 2022-07-18 [1] CRAN (R 4.1.3) #> insight 0.18.8 2022-11-24 [1] CRAN (R 4.1.3) #> knitr 1.42 2023-01-25 [1] CRAN (R 4.1.3) #> labelled 2.10.0 2022-09-14 [1] CRAN (R 4.1.3) #> lattice 0.20-45 2021-09-22 [1] CRAN (R 4.1.2) #> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.1.3) #> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.1.3) #> MASS 7.3-58.1 2022-08-03 [1] CRAN (R 4.1.3) #> Matrix 1.5-3 2022-11-11 [1] CRAN (R 4.1.3) #> multcomp 1.4-20 2022-08-07 [1] CRAN (R 4.1.3) #> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.0) #> mvtnorm 1.1-3 2021-10-08 [1] CRAN (R 4.1.1) #> parameters 0.20.0 2022-11-21 [1] CRAN (R 4.1.3) #> pillar 1.8.1 2022-08-19 [1] CRAN (R 4.1.3) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.0) #> purrr 1.0.1 2023-01-10 [1] CRAN (R 4.1.3) #> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.1.3) #> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.1.3) #> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.1.3) #> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.1.3) #> R6 2.5.1 2021-08-19 [1] CRAN (R 4.1.1) #> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.1.3) #> rlang 1.1.1 2023-04-28 [1] CRAN (R 4.1.2) #> rmarkdown 2.23 2023-07-01 [1] CRAN (R 4.1.2) #> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.1.3) #> sandwich 3.0-2 2022-06-15 [1] CRAN (R 4.1.3) #> scales 1.2.1 2022-08-20 [1] CRAN (R 4.1.3) #> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.1.3) #> stringi 1.7.6 2021-11-29 [1] CRAN (R 4.1.2) #> stringr 1.5.0 2022-12-02 [1] CRAN (R 4.1.3) #> styler 1.8.1 2022-11-07 [1] CRAN (R 4.1.3) #> survival * 3.4-0 2022-08-09 [1] CRAN (R 4.1.3) #> TH.data 1.1-1 2022-04-26 [1] CRAN (R 4.1.3) #> tibble 3.1.8 2022-07-22 [1] CRAN (R 4.1.3) #> tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.1.3) #> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.1.2) #> utf8 1.2.3 2023-01-31 [1] CRAN (R 4.1.3) #> vctrs 0.6.3 2023-06-14 [1] CRAN (R 4.1.2) #> withr 2.5.0 2022-03-03 [1] CRAN (R 4.1.2) #> xfun 0.37 2023-01-31 [1] CRAN (R 4.1.3) #> xtable 1.8-4 2019-04-21 [1] CRAN (R 4.0.0) #> yaml 2.3.7 2023-01-23 [1] CRAN (R 4.1.3) #> zoo 1.8-11 2022-09-17 [1] CRAN (R 4.1.3) #> #> [1] C:/Program Files/R/R-4.1.2/library #> #> ------------------------------------------------------------------------------ ```