analysis: Analysis wrapper function
In bayesCT: Simulation and Analysis of Adaptive Bayesian Clinical Trials

Wrapper function to analyze bayesian trials.

1	analysis(input, type = "binomial", .data = NULL)

`input`	list. Input function for all the analysis.
`type`	character. Type of analysis to be ran (binomial (default), normal. etc.).
`.data`	NULL. stores the all the details, please do not fill it in.

a list with results of the analysis of bayesian trial.

prob_of_accepting_alternative: scalar. The input parameter of probability of accepting the alternative.
margin: scalar. The margin input value of difference between mean estimate of treatment and mean estimate of the control.
alternative: character. The input parameter of alternative hypothesis.
N_treatment: scalar. The number of patients enrolled in the experimental group for each simulation.
N_control: scalar. The number of patients enrolled in the control group for each simulation.
N_enrolled: vector. The number of patients enrolled in the trial (sum of control and experimental group for each simulation. )
N_complete: scalar. The number of patients who completed the trial and had no loss to follow-up.
post_prob_accept_alternative: vector. The final probability of accepting the alternative hypothesis after the analysis is done.
est_final: scalar. The final estimate of the difference in posterior estimate of treatment and posterior estimate of the control group.
stop_futility: scalar. 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: scalar. Did the trial stop for early success during imputation of patient who had loss to follow up? 1 for yes and 0 for no.