Description Usage Arguments Value Examples
This is a modified version of get_cox_res
allowing for multiple runs
of get_cox_res.
1 2 | iter_get_cox_res(in.df, endpoint, endpoint.code, features,
broom.fun = c("tidy", "glance"), group = NULL)
|
in.df |
Input data.frame. |
endpoint |
Column name of the endpoint. |
endpoint.code |
Column name of the endpoint status code. |
features |
This must be a list of features. |
broom.fun |
Which broom function to run on the cox regression results. |
group |
Column name containing the groups to run cox regression on. If, specified, cox regression is run separately for each group. |
List of data frames with each data frame being the output of
get_cox_res
.
1 2 3 4 5 6 7 8 9 10 |
Detected multiple features. Running multivariate cox regression
Detected only one feature. Running univariate cox regression
# A tibble: 9 x 10
iter_num group term estimate std.error statistic p.value conf.low conf.high
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1 Obs age 1.00 0.00460 0.568 5.70e- 1 0.994 1.01
2 1 Obs obst~ 1.21 0.132 1.46 1.44e- 1 0.936 1.57
3 1 Lev age 1.00 0.00488 0.865 3.87e- 1 0.995 1.01
4 1 Lev obst~ 1.42 0.129 2.68 7.28e- 3 1.10 1.82
5 1 Lev+~ age 0.987 0.00519 -2.53 1.13e- 2 0.977 0.997
6 1 Lev+~ obst~ 1.08 0.168 0.484 6.29e- 1 0.781 1.51
7 2 Obs nodes 1.11 0.0106 10.0 1.04e-23 1.09 1.14
8 2 Lev nodes 1.07 0.0101 6.40 1.52e-10 1.05 1.09
9 2 Lev+~ nodes 1.11 0.0139 7.44 1.01e-13 1.08 1.14
# ... with 1 more variable: test_type <chr>
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