plot.OptGS_est: Plot point estimator performance for two-stage...

In mjg211/OptGS: Optimal and Near-optimal Group-sequential Designs for Clinical Trials with Continuous Outcomes

Description

plot.OptGS_est() plots (conditional and marginal) point estimator bias and residual mean squared error for a specified two-stage group-sequential clinical trial design.

Usage

## S3 method for class 'OptGS_est'
plot(x, ..., output = FALSE)

Arguments

x	An object of class OptGS_est, as returned by est.
...	For compatability with the generic.
output	A logical variable indicating whether to return output from the function.

Value

A list containing each of the input variables (subject to internal modification), along with the following elements:

• plots: A list containing the available plots.

See Also

est

Examples

# For the default two-stage design
plot(est(des = opt_gs(), tau = seq(-des$delta, 2*des$delta,
         length.out = 100)))

mjg211/OptGS documentation built on May 28, 2021, 3:44 p.m.