simulate: Simulation wrapper for binomial and normal.
In bayesCT: Simulation and Analysis of Adaptive Bayesian Clinical Trials

Wrapper function for complete binomial and normal function to compute power and type 1 error.

1	simulate(input, no_of_sim = 10000, .data = NULL)

`input`	list. Input function for all inputs in binomial and normal .
`no_of_sim`	numeric. Number of simulations to run
`.data`	NULL. stores the proportion of control and treatment, please do not fill it in.

a list with results of the simulation (power and type I error) and the input.

input: A list of input values used in the trial simulation.
power: data_frame. A data frame with the interim look and power at each look.
type1_error: scalar. The type 1 error or the number of times the trial rejects the null when the parameters are simulated under the null hypothesis.
est_final: vector. The final estimate of the difference in posterior estimate of treatment and posterior estimate of the control group for all the simulation.
post_prob_accept_alternative: vector. The final probability of accepting the alternative for the simulations.
N_enrolled: vector. The number of patients enrolled in the trial (sum of control and experimental group for each simulation.)
stop_futility: vector. Did the trial stop for futility during imputation of patient who had loss to follow up? 1 for yes and 0 for no.
stop_expected_success: vector. Did the trial stop for early success during imputation of patient who had loss to follow up? 1 for yes and 0 for no.