ezcox | R Documentation |
Run Cox Analysis in Batch Mode
ezcox(
data,
covariates,
controls = NULL,
time = "time",
status = "status",
global_method = c("likelihood", "wald", "logrank"),
keep_models = FALSE,
return_models = FALSE,
model_dir = file.path(tempdir(), "ezcox"),
verbose = TRUE,
...
)
data |
a |
covariates |
column names specifying variables. |
controls |
column names specifying controls.
The names with pattern "*:|()" will be treated as interaction/combination
term, please make sure all column names in |
time |
column name specifying time, default is 'time'. |
status |
column name specifying event status, default is 'status'. |
global_method |
method used to obtain global p value for cox model, should be one of "likelihood", "wald", "logrank". The likelihood-ratio test, Wald test, and score logrank statistics. These three methods are asymptotically equivalent. For large enough N, they will give similar results. For small N, they may differ somewhat. The Likelihood ratio test has better behavior for small sample sizes, so it is generally preferred. |
keep_models |
If |
return_models |
default |
model_dir |
a path for storing model results. |
verbose |
if |
... |
other parameters passing to |
a ezcox
object
Shixiang Wang w_shixiang@163.com
library(survival)
# Build unvariable models
t1 <- ezcox(lung, covariates = c("age", "sex", "ph.ecog"))
t1
# Build multi-variable models
# Control variable 'age'
t2 <- ezcox(lung, covariates = c("sex", "ph.ecog"), controls = "age")
t2
# Return models
t3 <- ezcox(lung,
covariates = c("age", "sex", "ph.ecog"),
return_models = TRUE
)
t3
t4 <- ezcox(lung,
covariates = c("sex", "ph.ecog"), controls = "age",
return_models = TRUE
)
t4
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