Description Usage Arguments Value Examples

View source: R/PowerBayesian.R

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".

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
)
``` |

`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 |

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

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
)
``` |

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