ddhazard_boot
Bootstrap for ddhazard
See the vignette 'Bootstrap illustration'. The do_stratify_with_event may be useful when either cases or non-cases are very rare to ensure that the model estimation succeeds.
Usage
ddhazard_boot(ddhazard_fit, strata, unique_id, R = 100,
do_stratify_with_event = F, do_sample_weights = F,
LRs = ddhazard_fit$control$LR * 2^(0:(-4)), print_errors = F)Arguments
- ddhazard_fit
Returned object from a
ddhazardcall- strata
Strata to sample within. These need to be on an individual by individual basis and not rows in the design matrix
- unique_id
Unique ids where entries match entries of
strata- R
Number of bootstrap estimates
- do_stratify_with_event
TRUEif sampling should be by strata of whether the individual has an event. An interaction factor will be made ifstratais provided- do_sample_weights
TRUEif weights should be sample instead of individuals- LRs
Learning rates in decreasing order which will be used to estimate the model.
- print_errors
TRUEif errors should be printed when estimations fails
Value
An object like returned from the boot function