Creates evaluation plot for decision boundary — decision

The function creates one plot for each given bound. It shows the confusion matrix for the mean of each bound. The function can be used to find which boundary for PRS best describes the data.

Usage

decision_cross(
  train_data,
  y,
  cross_folds,
  bounds,
  thr,
  ncores = 1,
  LogReg = FALSE
)

Arguments

train_data: List generated from gen_sim.
y: The target vector. Could either be estimated liabilities from LTFH or phenotypes.
cross_folds: Number of folds in cross validation.
bounds: Decision boundaries to plot outcome for.
thr: Threshold for p-value to be used in calculating PRS.
ncores: Amount of cores to be used.
LogReg: Boolean indicating if logistic regression should be used to estimate the casual effect.

Value

The confusion matrix for the mean of each bound.