Description Usage Arguments Value
Check the input values of function parameters for errors.
1 2 3 4 5 6 7 8 | checkInputs(ftime, ftype, trt, adjustVars, t0 = max(ftime[ftype > 0]),
SL.ftime = NULL, SL.ctime = NULL, SL.trt = NULL,
glm.ftime = NULL, glm.ctime = NULL, glm.trt = "1",
returnIC = TRUE, returnModels = TRUE,
ftypeOfInterest = unique(ftype[ftype != 0]),
trtOfInterest = unique(trt), method = "hazard", bounds = NULL,
verbose = FALSE, tol = 1/(length(ftime)), maxIter = 100,
Gcomp = FALSE)
|
ftime |
A numeric vector of failure times. Right-censored observations
should have corresponding |
ftype |
A numeric vector indicating the type of failure. Observations
with |
trt |
A numeric vector indicating observed treatment assignment. Each
unique value will be treated as an (unordered) separate type of
treatment. Currently, only two unique values of |
adjustVars |
A |
t0 |
The time at which to return cumulative incidence estimates. By
default this is set to |
SL.ftime |
A character vector or list specification to be passed to the
|
SL.ctime |
A character vector or list specification to be passed to the
|
SL.trt |
A character vector or list specification to be passed to the
|
glm.ftime |
A character specification of the right-hand side of the
equation passed to the |
glm.ctime |
A character specification of the right-hand side of the
equation passed to the |
glm.trt |
A character specification of the right-hand side of the
equation passed to the |
returnIC |
A boolean indicating whether to return vectors of influence
curve estimates. These are needed for some post-hoc comparisons, so it
is recommended to leave as |
returnModels |
A boolean indicating whether to return the
|
ftypeOfInterest |
An input specifying what failure types to compute
estimates of incidence for. The default value computes estimates for
values |
trtOfInterest |
An input specifying which levels of |
method |
A character specification of how the targeted minimum
loss-based estimators should be computer, either |
bounds |
A list of bounds. |
verbose |
A boolean indicating whether the function should print messages to indicate progress. |
tol |
The stopping criteria when |
maxIter |
A maximum number of iterations for the algorithm when
|
Gcomp |
A boolean indicating whether to compute the G-computation
estimator (i.e., a substitution estimator with no targeting step).
Note, theory does not support inference for the G-computation
estimator if Super Learner is used to estimate failure and censoring
mechanisms. Only implemented for |
Options to be passed to mean_tmle
or hazard_tmle
.
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