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Summarizes the efficacy and futility bounds for each analysis.

Usage

gs_bound_summary(x, alpha = NULL)

Arguments

x

design object

alpha

vector of alpha values to compute additional efficacy columns

Value

A data frame

Examples

library(gsDesign2)

x <- gs_design_ahr(info_frac = c(.25, .75, 1), analysis_time = c(12, 25, 36))
gs_bound_summary(x)
#>       Analysis               Value Efficacy Futility
#> 1    IA 1: 31%                   Z   3.8728  -1.6993
#> 2       N: 439         p (1-sided)   0.0001   0.9554
#> 3   Events: 99        ~HR at bound   0.4600   1.4060
#> 4    Month: 12    P(Cross) if HR=1   0.0001   0.0446
#> 5              P(Cross) if AHR=0.8   0.0025   0.0032
#> 6    IA 2: 77%                   Z   2.3100   1.0889
#> 7       N: 527         p (1-sided)   0.0104   0.1381
#> 8  Events: 248        ~HR at bound   0.7455   0.8707
#> 9    Month: 25    P(Cross) if HR=1   0.0105   0.8620
#> 10             P(Cross) if AHR=0.7   0.6348   0.0599
#> 11       Final                   Z   2.0161   2.0143
#> 12      N: 527         p (1-sided)   0.0219   0.0220
#> 13 Events: 323        ~HR at bound   0.7990   0.7992
#> 14   Month: 36    P(Cross) if HR=1   0.0243   0.9756
#> 15             P(Cross) if AHR=0.7   0.9000   0.1001

x <- gs_design_wlr(info_frac = c(.25, .75, 1), analysis_time = c(12, 25, 36))
gs_bound_summary(x)
#>       Analysis                Value Efficacy Futility
#> 1    IA 1: 25%                    Z   4.2955  -2.0871
#> 2       N: 436          p (1-sided)   0.0000   0.9816
#> 3   Events: 99         ~HR at bound   0.4213   1.5219
#> 4    Month: 12     P(Cross) if HR=1   0.0000   0.0184
#> 5              P(Cross) if wAHR=0.8   0.0004   0.0012
#> 6    IA 2: 76%                    Z   2.3156   1.1034
#> 7       N: 523          p (1-sided)   0.0103   0.1349
#> 8  Events: 246         ~HR at bound   0.7442   0.8687
#> 9    Month: 25     P(Cross) if HR=1   0.0103   0.8651
#> 10             P(Cross) if wAHR=0.7   0.6323   0.0610
#> 11       Final                    Z   2.0151   2.0151
#> 12      N: 523          p (1-sided)   0.0219   0.0219
#> 13 Events: 321         ~HR at bound   0.7985   0.7985
#> 14   Month: 36     P(Cross) if HR=1   0.0242   0.9758
#> 15             P(Cross) if wAHR=0.7   0.9000   0.1000

# Report multiple efficacy bounds (only supported for AHR designs)
x <- gs_design_ahr(analysis_time = 1:3*12, alpha = 0.0125)
gs_bound_summary(x, alpha = c(0.025, 0.05))
#>       Analysis               Value α=0.0125 α=0.025 α=0.05 Futility
#> 1    IA 1: 31%                   Z   4.3506  3.8728 3.3437  -1.6192
#> 2       N: 509         p (1-sided)   0.0000  0.0001 0.0004   0.9473
#> 3  Events: 115        ~HR at bound   0.4449  0.4863 0.5366   1.3518
#> 4    Month: 12    P(Cross) if HR=1   0.0000  0.0001 0.0004   0.0527
#> 5              P(Cross) if AHR=0.8   0.0007  0.0032 0.0139   0.0032
#> 6    IA 2: 74%                   Z   2.6778  2.3579 2.0022   1.1590
#> 7       N: 611         p (1-sided)   0.0037  0.0092 0.0226   0.1232
#> 8  Events: 278        ~HR at bound   0.7251  0.7535 0.7863   0.8701
#> 9    Month: 24    P(Cross) if HR=1   0.0037  0.0092 0.0228   0.8768
#> 10             P(Cross) if AHR=0.7   0.5336  0.6571 0.7770   0.0556
#> 11       Final                   Z   2.2781  2.0096 1.7134   2.2775
#> 12      N: 611         p (1-sided)   0.0114  0.0222 0.0433   0.0114
#> 13 Events: 375        ~HR at bound   0.7903  0.8125 0.8378   0.7903
#> 14   Month: 36    P(Cross) if HR=1   0.0122  0.0237 0.0445   0.9878
#> 15             P(Cross) if AHR=0.7   0.9000  0.9252 0.9390   0.1001