# PowerBayesian: Power Calculation for a SMART with a Binary Outcome In SMARTbayesR: Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs for Binary Outcomes

## Description

This function computes the power for a sequential multiple assignment randomized trial (SMART) of one of three designs: "design-1" or "general" or "design-3".

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```PowerBayesian( design = "design-1", sample_size = 100, response_prob = c(0.5, 0.9, 0.3, 0.7, 0.5, 0.8), stage_one_trt_one_response_prob = 0.7, stage_one_trt_two_response_prob = 0.5, stage_one_trt_three_response_prob = 0.4, type = "log-OR", threshold, alpha = 0.05 ) ```

## Arguments

 `design` specifies for which SMART design to calculate the power: design-1, general, or design-3. `sample_size` the total SMART study sample size. `response_prob` a vector of probabilities of response for each of embedded treatment sequences. In the case of design 1, there are 6, for general design there are 8, and for design-3 there are 9 `stage_one_trt_one_response_prob` the probability of response to stage-1 treatment for first stage-1 treatment. `stage_one_trt_two_response_prob` the probability of response to stage-1 treatment for second stage-1 treatment. `stage_one_trt_three_response_prob` the probability of response to stage-1 treatment for third stage-1 treatment (for design-3 only). `type` specifies log-OR, RD or log-RR. `threshold` minimum detectable difference between each EDTR and the best `alpha` probability of excluding optimal embedded dynamic treatment regime

## Value

The power to exclude embedded dynamic treatment regimes bigger than threshold from the set of best.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```PowerBayesian( design = "design-1", sample_size = 100, response_prob = c(0.5, 0.9, 0.3, 0.7, 0.5, 0.8), stage_one_trt_one_response_prob = 0.7, stage_one_trt_two_response_prob = 0.5, type="log-OR", threshold=0.2 ) PowerBayesian( design = "general", sample_size = 250, response_prob = c(0.5, 0.9, 0.7, 0.2, 0.3, 0.8, 0.4, 0.7), stage_one_trt_one_response_prob = 0.7, stage_one_trt_two_response_prob = 0.5, type="log-OR", threshold=0.2 ) ```

SMARTbayesR documentation built on Oct. 1, 2021, 1:06 a.m.