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23 | 23 | #' @param ratio Experimental:Control randomization ratio.
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24 | 24 | #' @param alpha One-sided Type I error.
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25 | 25 | #' @param beta Type II error.
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26 |
| -#' @param info_frac Targeted information fraction at each analysis. |
27 |
| -#' @param analysis_time Minimum time of analysis. |
| 26 | +#' @param info_frac Targeted information fraction at each analysis. See details for properly set it up. |
| 27 | +#' @param analysis_time Targeted time of analysis. See details for properly set it up. |
28 | 28 | #' @param binding Indicator of whether futility bound is binding;
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29 | 29 | #' default of `FALSE` is recommended.
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30 | 30 | #' @param upper Function to compute upper bound.
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31 |
| -#' - \code{gs_b()}: fixed efficacy bounds. |
32 | 31 | #' - \code{gs_spending_bound()}: alpha-spending efficacy bounds.
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| 32 | +#' - \code{gs_b()}: fixed efficacy bounds. |
33 | 33 | #' @param upar Parameters passed to `upper`.
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34 | 34 | #' - If `upper = gs_b`, then `upar` is a numerical vector specifying the fixed efficacy bounds per analysis.
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35 | 35 | #' - If `upper = gs_spending_bound`, then `upar` is a list including
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36 | 36 | #' - `sf` for the spending function family.
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37 | 37 | #' - `total_spend` for total alpha spend.
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38 | 38 | #' - `param` for the parameter of the spending function.
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39 | 39 | #' - `timing` (not required for information-based spending) for the spending time if different from information-based spending.
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40 |
| -#' @param lower Function to compute lower bound, which can be set up similarly as `upper.` |
| 40 | +#' @param lower Function to compute lower bound, which can be set up similarly as `upper`. More details can be find in [this vignette](https://merck.github.io/gsDesign2/articles/story-seven-test-types.html). |
41 | 41 | #' @param lpar Parameters passed to `lower`, which can be set up similarly as `upar.`
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42 | 42 | #' @param info_scale Information scale for calculation. Options are:
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43 | 43 | #' - `"h0_h1_info"` (default): variance under both null and alternative hypotheses is used.
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71 | 71 | #' - The `analysis` is a table summarizing the analysis time, sample size, events, average HR, treatment effect and statistical information per analysis.
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72 | 72 | #' @export
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73 | 73 | #'
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| 74 | +#' @details |
| 75 | +#' The parameters `info_frac` and `analysis_time` are used to determine the timing for interim and final analyses. |
| 76 | +#' - If the interim analysis is decided by targeted information fraction and the study duration is known, |
| 77 | +#' then `info_frac` is a numerical vector where each element (greater than 0 and less than or equal to 1) |
| 78 | +#' represents the information fraction for each analysis. |
| 79 | +#' The `analysis_time`, which defaults to 36, indicates the time for the final analysis. |
| 80 | +#' - If the interim analysis is determined solely by the targeted analysis timing, |
| 81 | +#' then `analysis_time` will be a vector specifying the time for each analysis. |
| 82 | +#' - If both the targeted analysis time and the targeted information fraction are utilized, which arrives latter, |
| 83 | +#' then both `info_frac` and `analysis_time` should be provided as vectors. |
| 84 | +#' |
74 | 85 | #' @examples
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75 | 86 | #' library(gsDesign)
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76 | 87 | #' library(gsDesign2)
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