Convert a summary table object to a gt object

Convert a summary table object created with as_table to a gt_tbl object; currently only implemented for gsBinomialExact.

Usage

as_gt(x, ...)

# S3 method for class 'gsBinomialExactTable'
as_gt(
  x,
  ...,
  title = "Operating Characteristics for the Truncated SPRT Design",
  subtitle = "Assumes trial evaluated sequentially after each response",
  theta_label = html("Underlying<br>response rate"),
  bound_label = c("Futility bound", "Efficacy bound"),
  prob_decimals = 2,
  en_decimals = 1,
  rr_decimals = 0
)

Arguments

x: Object to be converted.
...: Other parameters that may be specific to the object.
title: Table title.
subtitle: Table subtitle.
theta_label: Label for theta.
bound_label: Label for bounds.
prob_decimals: Number of decimal places for probability of crossing.
en_decimals: Number of decimal places for expected number of observations when bound is crossed or when trial ends without crossing.
rr_decimals: Number of decimal places for response rates.

Value

A gt_tbl object that may be extended by overloaded versions of as_gt.

Details

Currently only implemented for gsBinomialExact objects. Creates a table to summarize an object. For gsBinomialExact, this summarized operating characteristics across a range of effect sizes.

Examples

safety_design <- binomialSPRT(
  p0 = .04, p1 = .1, alpha = .04, beta = .2, minn = 4, maxn = 75
)
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")
  )


  Operating Characteristics for the Truncated SPRT Design
    
Assumes trial evaluated sequentially after each response
    
Underlying
AE rate
      
        Probability of crossing
      
      Average
sample size
    
low rate
      high rate
    
2%
0.964
0.001
34.8
4%
0.769
0.019
46.4
6%
0.506
0.108
54.3
8%
0.291
0.290
56.1
10%
0.155
0.516
52.8
12%
0.079
0.714
46.8
14%
0.039
0.851
40.2
16%
0.020
0.930
34.2