Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

# S3 method for survdiff
tidy(x, ...)

Arguments

x

An survdiff object returned from survival::survdiff().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

See also

Value

A tibble::tibble() with columns:

exp

weighted expected number of events in each group

N

number of subjects in each group

obs

weighted observed number of events in each group

Examples

library(survival) s <- survdiff( Surv(time, status) ~ pat.karno + strata(inst), data = lung ) tidy(s)
#> # A tibble: 8 x 4 #> pat.karno N obs exp #> <chr> <dbl> <dbl> <dbl> #> 1 30 2 1 0.692 #> 2 40 2 1 1.10 #> 3 50 4 4 1.17 #> 4 60 30 27 16.3 #> 5 70 41 31 26.4 #> 6 80 50 38 41.9 #> 7 90 60 38 47.2 #> 8 100 35 21 26.2
#> # A tibble: 1 x 3 #> statistic df p.value #> <dbl> <dbl> <dbl> #> 1 21.4 7 0.00326