BwB.HRandIndex.param: Bootstrap Estimation of Hazard Function and Index Parameters

Description

Performs bootstrap estimation of hazard rates and their standard deviation at each grid point (double boostrap) together with the corresponding index parameters for a given set of bootstrap samples. The output of the function is used as input in StudentizedBwB.Index.CIs.

Usage

BwB.HRandIndex.param(B, B1, Boot.samples, marker_name1, marker_name2, 
                            event_time_name, time_name, event_name, b, t, true.haz, 
                            v.param,  hqm.est, id, xin)

Value

A list of matrices of dimension n.est.points × B containing the bootstrap hazard estimates, the logarithm of the hazard rate estimates and and two vectors of the estimate's standard deviations at each grid point.

Arguments

B: Integer. Number of bootstrap samples.
B1: Integer. Number of bootstrap re-samples.
Boot.samples: A list of bootstrap datasets. Each element corresponds to one replicate.
marker_name1: Character string. Name of the first longitudinal marker.
marker_name2: Character string. Name of the second longitudinal marker.
event_time_name: Name of the event time variable in the data.
time_name: Name of the time variable for the longitudinal marker measurements.
event_name: Name of the event indicator variable.
b: Numeric. Bandwidth parameter used in hazard estimation.
t: Numeric. Evaluation point for the conditional hazard.
true.haz: Numeric vector. The true or reference hazard used in the optimisation criterion.
v.param: Numeric vector. Starting values of the indexing parameters for the optimisation of the index coefficients.
hqm.est: HQM estimator on the original sample.
id: label of id variable of dataset.
xin: original sample.

Details

For each bootstrap iteration \(k = 1, \dots, B\), the function:

Extracts the bootstrap sample data.use.
Computes centred marker values at the subject and observation level.
Estimates index parameters by minimising index_optim using optim.
Computes the bootstrap hazard estimate via Boot.hqm.

The outputs are matrices collecting the hazard estimates and estimated index parameter vectors across bootstrap replicates.

Examples

Run this code

  
# See the example for  function: StudentizedBwB.Index