Nothing
## ----include=FALSE--------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
dev = "ragg_png",
dpi = 96,
fig.retina = 1,
fig.width = 7.2916667,
fig.asp = 0.618,
fig.align = "center",
out.width = "80%"
)
## ----warning=FALSE, message=FALSE-----------------------
library(gsDesign)
## -------------------------------------------------------
b <- binomialSPRT(p0 = .1, p1 = .35, alpha = .08, beta = .2, minn = 10, maxn = 25)
plot(b)
## ----warning=FALSE, message=FALSE-----------------------
library(ggplot2)
## -------------------------------------------------------
p <- plot(b, plottype = 2)
p + scale_y_continuous(breaks = seq(0, 90, 10))
## ----warning=FALSE, message=FALSE-----------------------
library(dplyr)
library(tidyr)
## -------------------------------------------------------
# Compute boundary crossing probabilities for selected response rates
b_power <- gsBinomialExact(
k = length(b$n.I), theta = seq(.1, .45, .05), n.I = b$n.I,
a = b$lower$bound, b = b$upper$bound
)
## -------------------------------------------------------
b_power %>%
as_table() %>%
as_gt()
## -------------------------------------------------------
safety_design <- binomialSPRT(p0 = .04, p1 = .1, alpha = .04, beta = .2, minn = 4, maxn = 75)
plot(safety_design)
## -------------------------------------------------------
plot(safety_design, plottype = 2)
## -------------------------------------------------------
safety_power <- gsBinomialExact(
k = length(safety_design$n.I),
theta = seq(.02, .16, .02),
n.I = safety_design$n.I,
a = safety_design$lower$bound,
b = safety_design$upper$bound
)
safety_power %>%
as_table() %>%
as_gt(
theta_label = gt::html("Underlying<br>AE rate"),
prob_decimals = 3,
bound_label = c("low rate", "high rate")
)
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