aspre_k2: Cost estimating function in ASPRE simulation

In OptHoldoutSize: Estimation of Optimal Size for a Holdout Set for Updating a Predictive Score

Cost estimating function in ASPRE simulation

Description

Estimate cost at a given holdout set size in ASPRE model

Usage

aspre_k2(
  n,
  X,
  PRE,
  seed = NULL,
  pi_PRE = 1426/58974,
  pi_intervention = 0.1,
  alpha = 0.37
)

Arguments

n	Holdout set size at which to estimate k_2 (cost)
X	Matrix of predictors
PRE	Vector indicating PRE incidence
seed	Random seed; set before starting or set to NULL
pi_PRE	Population prevalence of PRE if not prophylactically treated. Defaults to empirical value 1426/58974
pi_intervention	Proportion of the population on which an intervention will be made. Defaults to 0.1
alpha	Reduction in PRE risk with intervention. Defaults to empirical value 0.37

Value

Estimated cost

Examples

# Simulate
set.seed(32142)

N=1000; p=15
X=matrix(rnorm(N*p),N,p); PRE=rbinom(N,1,prob=logit(X%*% rnorm(p)))
aspre_k2(1000,X,PRE)

OptHoldoutSize documentation built on April 12, 2025, 1:34 a.m.