get_draws_norm: Generate draws from posterior normal distributions
In adaptr: Adaptive Trial Simulator

get_draws_norm

R Documentation

Generate draws from posterior normal distributions

Description

Used internally. This function generates draws from posterior, normal distributions for continuous outcomes. Technically, these posteriors use no priors (for simulation speed), corresponding to the use of improper flat priors. These posteriors correspond (and give similar results) to using normal-normal models (normally distributed outcome, conjugate normal prior) for each arm, assuming that a non-informative, flat prior is used. Thus, the posteriors directly correspond to normal distributions with each groups' mean as the mean and each groups' standard error as the standard deviation. As it is necessary to always return valid draws, in cases where ⁠< 2⁠ patients have been randomised to an arm, posterior draws will come from an extremely wide normal distribution with mean corresponding to the mean of all included patients with outcome data and a standard deviation corresponding to the difference between the highest and lowest recorded outcomes for all patients with available outcome data multiplied by 1000.

Usage

get_draws_norm(arms, allocs, ys, control, n_draws)

Arguments

`arms`	character vector, currently active `arms` as specified in `setup_trial()` / `setup_trial_binom()` / `setup_trial_norm()`.
`allocs`	character vector, allocations of all patients (including allocations to currently inactive `arms`).
`ys`	numeric vector, outcomes of all patients in the same order as `alloc` (including outcomes of patients in currently inactive `arms`).
`control`	unused argument in the built-in functions for `setup_trial_binom()` and setup_trial_norm, but required as this argument is supplied by the `run_trial()` function, and may be used in user-defined functions used to generate posterior draws.
`n_draws`	single integer, number of posterior draws.