Generate the list of estimators and p-values that were used in the paper
get_statistics_from_paper.Rd
Generate the list of estimators and p-values that were used in the paper
Usage
get_statistics_from_paper(
point_estimators = TRUE,
interval_estimators = TRUE,
p_values = TRUE
)
Value
a list of PointEstimator
s, IntervalEstimator
s and
PValue
.
Examples
set.seed(123)
dat <- data.frame(
endpoint = c(rnorm(28, 0.3)),
stage = rep(1, 28)
)
analyze(data = dat,
statistics = list(),
data_distribution = Normal(FALSE),
design = get_example_design(),
sigma = 1)
#> Design: TwoStageDesign<n1=28;0.8<=x1<=2.3:n2=9-40>
#> Data Distribution: Normal<single-armed>
#> Observed number of stages: 1
#> Observed n1 (total) 28
#> Z1 1.3
#> Interim decision: continue to second stage
#> Calculated n2(Z1) (per group) 32.21129
#> Calculated c2(Z1) 1.71
#>
# The results suggest recruiting 32 patients for the second stage
dat <- rbind(
dat,
data.frame(
endpoint = rnorm(32, mean = 0.3),
stage = rep(2, 32)))
analyze(data = dat,
statistics = get_example_statistics(),
data_distribution = Normal(FALSE),
design = get_example_design(),
sigma = 1)
#> Design: TwoStageDesign<n1=28;0.8<=x1<=2.3:n2=9-40>
#> Data Distribution: Normal<single-armed>
#> Observed number of stages: 2
#> Observed n1 (total) 28
#> Z1 1.3
#> Interim decision: continue to second stage
#> Calculated n2(Z1) (per group) 32.21129
#> Calculated c2(Z1) 1.71
#> Observed n2 (in total) 32
#> Z2 2.66
#> Final test decision: reject null
#>
#> Stage 2 results:
#> Sample mean: 0.3656173
#> Pseudo Rao-Blackwellized: 0.3135628
#> Median unbiased (LR test ordering): 0.3420742
#> Bias reduced MLE (iterations=1): 0.357214
#> SWCF ordering CI: [0.04664821, 0.6142449]
#> LR test ordering CI: [0.08992822, 0.6106096]
#> SWCF ordering p-value: 0.01321363
#> LR test ordering p-value: 0.003551316
#>