| as_tibble.simulations_collection {escalation} | R Documentation |
Convert a simulations_collection to a tibble
Description
Cumulative statistics are shown to gauge how the simulations converge.
Usage
## S3 method for class 'simulations_collection'
as_tibble(x, target_dose = NULL, alpha = 0.05, ...)
Arguments
x |
object of type |
target_dose |
numerical dose index, or NULL (default) for all doses |
alpha |
significance level for symmetrical confidence intervals |
... |
extra args are ignored |
Value
a tibble with cols:
-
dose, the dose-level -
n, cumulative inference using the first n simulated iterations -
design.x, The first design in the comparison, aka design X -
hit.x, logical showing if design X recommended dose in iterate n -
design.y, The second design in the comparison, aka design Y -
hit.x, logical showing if design Y recommended dose in iterate n -
X, cumulative sum of hit.x within dose, i.e. count of recommendations -
X2, cumulative sum of hit.x^2 within dose -
Y, cumulative sum of hit.y within dose, i.e. count of recommendations -
Y2, cumulative sum of hit.y^2 within dose -
XY, cumulative sum of hit.x * hit.y within dose -
psi1, X / n -
psi2, Y / n -
v_psi1, variance of psi1 -
v_psi2, variance of psi2 -
cov_psi12, covariance of psi1 and psi2 -
delta, psi1 - psi2 -
v_delta, variance of delta -
se_delta, standard error of delta -
delta_l, delta - q * se_delta, where q is alpha / 2 normal quantile -
delta_u, delta + q * se_delta, where q is alpha / 2 normal quantile -
comparison, Label of design.x vs design.y, using design names