Description
The CoxSurvival function takes as input the coefficient and linear
prediction tbl_teradata generated by the function CoxPH (td_coxph_mle
)
and outputs a tbl_teradata of survival probabilities.
Usage
td_cox_survival_mle (
object = NULL,
cox.model.table = NULL,
predict.table = NULL,
predict.feature.names = NULL,
predict.feature.columns = NULL,
accumulate = NULL,
cox.model.table.sequence.column = NULL,
object.sequence.column = NULL,
predict.table.sequence.column = NULL
)
Arguments
object |
Required Argument. |
cox.model.table |
Required Argument. |
predict.table |
Required Argument. |
predict.feature.names |
Required Argument. |
predict.feature.columns |
Required Argument. |
accumulate |
Optional Argument. |
cox.model.table.sequence.column |
Optional Argument. |
object.sequence.column |
Optional Argument. |
predict.table.sequence.column |
Optional Argument. |
Value
Function returns an object of class "td_cox_survival_mle" which is a
named list containing objects of class "tbl_teradata".
Named list members can be referenced directly with the "$" operator
using following names:
survival.probability
-
output
Examples
# Get the current context/connection
con <- td_get_context()$connection
# Load example data.
loadExampleData("coxsurvival_example", "lungcancer","lc_new_predictors")
# Create object(s) of class "tbl_teradata".
lungcancer <- tbl(con, "lungcancer")
lc_new_predictors <- tbl(con, "lc_new_predictors")
td_coxph_out <- td_coxph_mle(data = lungcancer,
feature.columns = c("trt","celltype","karno","diagtime","age","prior"),
time.interval.column = "time_int",
event.column = "status",
categorical.columns = c("trt","celltype","prior")
)
# Linear model predictor tbl_teradata and coefficient tbl_teradata that are generated from
# the td_coxph_mle() function are used to determine the survival probabilities of
# the new patients.
# Example 1 - Pass generated coefficient tbl_teradata and linear predictor tbl_teradata.
td_cox_survival_out <- td_cox_survival_mle(object = td_coxph_out$coefficient.table,
cox.model.table = td_coxph_out$linear.predictor.table,
predict.table = lc_new_predictors,
predict.feature.names = c("trt", "celltype", "karno",
"diagtime", "age", "prior"),
predict.feature.columns = c("trt", "celltype", "karno",
"diagtime", "age", "prior"),
accumulate = c("id", "name")
)
# Example 2 - Pass output of td_coxph_mle() directly as object argument.
td_cox_survival_out <- td_cox_survival_mle(object = td_coxph_out,
cox.model.table = td_coxph_out$linear.predictor.table,
predict.table = lc_new_predictors ,
predict.feature.names = c("trt", "celltype", "karno",
"diagtime", "age", "prior"),
predict.feature.columns = c("trt", "celltype", "karno",
"diagtime", "age", "prior"),
accumulate = c("id", "name")
)