phat {DesignCTPB}

Point estimator for the power value

Description

This function is to estimate the power values given fixed proportion r for each sub-population, which we utilize Monte Carlo method and GPU accelerator to estimate the power value. The user can specify the standard deviation and harzard reduction for each sub-population as the prior information of harzard reduction distribution, when not specified, we apply a default setting of linear harzard reduction scheme and the sd for each sub-population is inversely proportional to sqrt(r_i)

Usage

phat(
  r,
  N1,
  N2,
  N3,
  E = NULL,
  sig = NULL,
  sd_full,
  delta = NULL,
  delta_linear_bd,
  seed = NULL
)

Arguments

r

vector for the proportion for each sub-population, r_1is 1, r_i>r_i+1

N1

integer, which is fixed as 10240 in our package

N2

integer, which is fixed as 20480 in our package

N3

integer, the number of grid point for the sig.lv, which should be the multiples of 5, because we apply 5 stream parallel

E

integer, the total number of events for the Phase 3 clinical trail, if not specified, then an estimation will be applied

sig

the vector of standard deviation of each sub-population

sd_full

a numeric number, which denotes the prior information of standard deviation for the harzard reduction. If sig is not specified, then sd_full must has an input value to define the standard deviation of the full population

delta

vector, the point estimation of harzard reduction in prior information, if not specified we apply a linear scheme by giving bound to the linear harzard reduction

delta_linear_bd

vector of length 2, specifying the upper bound and lower bound for the harzard reduction; if user don't specify the delta for each sub-population, then the linear scheme will apply and the input is a must.

seed

integer, seed for random number generation

Details

We interface python by reticulate package to utilize numba(cuda version) module to accelerate calculation.

Value

list of 2 parts of the sampling points given specific r; alpha is the matrix as each row is the given sig.lv for each population; power is the corresponding power values given each row of the alpha