A method that updates existing DataDA
object with new data.
Usage
# S4 method for class 'DataDA'
update(object, u, t0, trialtime, y, ..., check = TRUE)
Arguments
- object
(
DataDA
)
object you want to update.- u
(
numeric
)
the new DLT free survival times for all patients, i.e. for existing patients in theobject
as well as for new patients.- t0
(
numeric
)
the time that each patient starts DLT observation window. This parameter covers all patients, i.e. existing patients in theobject
as well as for new patients.- trialtime
(
number
)
current time in the trial, i.e. a followup time.- y
(
numeric
)
the new DLTs for all patients, i.e. for existing patients in theobject
as well as for new patients.- ...
further arguments passed to
Data
update methodupdate-Data
. These are used when there are new patients to be added to the cohort.- check
(
flag
)
whether the validation of the updated object should be conducted. See help forupdate-Data
for more details on the use case of this parameter.
Value
The new, updated DataDA
object.
Note
This function is capable of not only adding new patients but also
updates existing ones with respect to y
, t0
, u
slots.
Examples
# Create an object of class 'DataDA'.
my_data <- DataDA(
x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
y = c(0, 0, 1, 1, 0, 0, 1, 0),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2)),
u = c(42, 30, 15, 5, 20, 25, 30, 60),
t0 = c(0, 15, 30, 40, 55, 70, 75, 85),
Tmax = 60
)
#> Used default patient IDs!
#> Used best guess cohort indices!
# Update the data.
my_data1 <- update(
object = my_data,
y = c(my_data@y, 0), # The 'y' will be updated according to 'u'.
u = c(my_data@u, 20),
t0 = c(my_data@t0, 95),
x = 20,
trialtime = 120 # This is the global timeline for a trial.
)
my_data1
#> An object of class "DataDA"
#> Slot "u":
#> [1] 42 30 15 5 20 25 30 35 20
#>
#> Slot "t0":
#> [1] 0 15 30 40 55 70 75 85 95
#>
#> Slot "Tmax":
#> [1] 60
#>
#> Slot "x":
#> [1] 0.1 0.5 1.5 3.0 6.0 10.0 10.0 10.0 20.0
#>
#> Slot "y":
#> [1] 0 0 1 1 0 0 1 0 0
#>
#> Slot "doseGrid":
#> [1] 0.1 0.5 1.5 3.0 6.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0 24.0 26.0 28.0
#> [16] 30.0 32.0 34.0 36.0 38.0 40.0 42.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0
#> [31] 60.0 62.0 64.0 66.0 68.0 70.0 72.0 74.0 76.0 78.0 80.0
#>
#> Slot "nGrid":
#> [1] 41
#>
#> Slot "xLevel":
#> [1] 1 2 3 4 5 6 6 6 11
#>
#> Slot "placebo":
#> [1] FALSE
#>
#> Slot "ID":
#> [1] 1 2 3 4 5 6 7 8 9
#>
#> Slot "cohort":
#> [1] 1 2 3 4 5 6 6 6 7
#>
#> Slot "nObs":
#> [1] 9
#>