R broom tidy.cch 整理 a(n) cch 對象

# S3 method for cch
tidy(x, conf.level = 0.95, ...)

tidy() , survival::cch()

其他 cch 整理器：glance.cch() 、glance.survfit()

其他生存整理器：augment.coxph() , augment.survreg() , glance.aareg() , glance.cch() , glance.coxph() , glance.pyears() , glance.survdiff() , glance.survexp() , glance.survfit() , glance.survreg() , tidy.aareg() , tidy.coxph() , tidy.pyears() , tidy.survdiff() , tidy.survexp() , tidy.survfit() , tidy.survreg()

# load libraries for models and data
library(survival)

# examples come from cch documentation
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

# fit model
fit.ccP <- cch(Surv(edrel, rel) ~ stage + histol + age,
  data = ccoh.data,
  subcoh = ~subcohort, id = ~seqno, cohort.size = 4028
)

# summarize model fit with tidiers + visualization
tidy(fit.ccP)
#> # A tibble: 5 × 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

# coefficient plot
library(ggplot2)

ggplot(tidy(fit.ccP), aes(x = estimate, y = term)) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high), height = 0) +
  geom_vline(xintercept = 0)