Axing a coxph.
Arguments
- x
A model object.
- verbose
Print information each time an axe method is executed. Notes how much memory is released and what functions are disabled. Default is
FALSE.- ...
Any additional arguments related to axing.
Examples
library(survival)
example_data <-
tibble::tibble(
time = rpois(1000, 2) + 1,
status = rbinom(1000, 1, .5),
x = rpois(1000, .5),
covar = rbinom(1000, 1, .5)
)
example_data
#> # A tibble: 1,000 × 4
#> time status x covar
#> <dbl> <int> <int> <int>
#> 1 4 0 5 1
#> 2 2 1 0 1
#> 3 2 0 0 0
#> 4 3 0 0 0
#> 5 1 0 0 1
#> 6 4 1 1 0
#> 7 3 1 0 1
#> 8 1 1 1 0
#> 9 5 0 0 0
#> 10 3 1 0 1
#> # … with 990 more rows
make_big_model <- function() {
boop <- runif(1e6)
coxph(Surv(time, status) ~ x + strata(covar), example_data)
}
res <- make_big_model()
weigh(res)
#> # A tibble: 20 × 2
#> object size
#> <chr> <dbl>
#> 1 terms 8.15
#> 2 formula 8.15
#> 3 residuals 0.0722
#> 4 y 0.0177
#> 5 linear.predictors 0.00805
#> 6 call 0.00146
#> 7 concordance 0.000752
#> 8 coefficients 0.00028
#> 9 means 0.00028
#> 10 wald.test 0.00028
#> 11 var 0.000224
#> 12 xlevels.strata(covar) 0.000176
#> 13 method 0.000112
#> 14 loglik 0.000064
#> 15 score 0.000056
#> 16 iter 0.000056
#> 17 n 0.000056
#> 18 nevent 0.000056
#> 19 assign.x 0.000056
#> 20 timefix 0.000056
weigh(butcher(res))
#> # A tibble: 20 × 2
#> object size
#> <chr> <dbl>
#> 1 terms 8.15
#> 2 residuals 0.0722
#> 3 linear.predictors 0.00805
#> 4 formula 0.00149
#> 5 call 0.00146
#> 6 concordance 0.000752
#> 7 coefficients 0.00028
#> 8 means 0.00028
#> 9 wald.test 0.00028
#> 10 var 0.000224
#> 11 xlevels.strata(covar) 0.000176
#> 12 method 0.000112
#> 13 loglik 0.000064
#> 14 score 0.000056
#> 15 iter 0.000056
#> 16 n 0.000056
#> 17 nevent 0.000056
#> 18 assign.x 0.000056
#> 19 timefix 0.000056
#> 20 y 0.000048