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Save a summary table object as an RTF file

Source: R/as_rtf.R
as_rtf.Rd

Convert and save the summary table object created with as_table to an RTF file using r2rtf; currently only implemented for gsBinomialExact.

Usage

as_rtf(x, ...)

# S3 method for class 'gsBinomialExactTable'
as_rtf(
  x,
  file,
  ...,
  title = paste("Operating Characteristics by Underlying Response Rate for",
    "Exact Binomial Group Sequential Design"),
  theta_label = "Underlying Response Rate",
  response_outcome = TRUE,
  bound_label = if (response_outcome) c("Futility Bound", "Efficacy Bound") else
    c("Efficacy Bound", "Futility Bound"),
  en_label = "Expected Sample Sizes",
  prob_decimals = 2,
  en_decimals = 1,
  rr_decimals = 0
)

# S3 method for class 'gsBoundSummary'
as_rtf(
  x,
  file,
  ...,
  title = "Boundary Characteristics for Group Sequential Design",
  footnote_p_onesided = "one-side p-value for experimental better than control",
  footnote_appx_effect_at_bound = NULL,
  footnote_p_cross_h0 = "Cumulative type I error assuming binding futility bound",
  footnote_p_cross_h1 = "Cumulative power under the alternate hypothesis",
  footnote_specify = NULL,
  footnote_text = NULL
)

Arguments

x

Object to be saved as RTF file.

...

Other parameters that may be specific to the object.

file

File path for the output.

title

Title of the report.

theta_label

Label for theta.

response_outcome

Logical values indicating if the outcome is response rate (TRUE) or failure rate (FALSE). The default value is TRUE.

bound_label

Label for bounds. If the outcome is response rate, then the label is "Futility bound" and "Efficacy bound". If the outcome is failure rate, then the label is "Efficacy bound" and "Futility bound".

en_label

Label for expected number.

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.

footnote_p_onesided

Footnote for one-side p-value.

footnote_appx_effect_at_bound

Footnote for approximate effect treatment at bound.

footnote_p_cross_h0

Footnote for cumulative type I error.

footnote_p_cross_h1

Footnote for cumulative power under the alternate hypothesis.

footnote_specify

Vector of string to put footnote super script.

footnote_text

Vector of string of footnote text.

Value

as_rtf() returns the input x invisibly.

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.

See also

vignette("binomialSPRTExample")

Examples

# as_rtf for gsBinomialExact
zz <- gsBinomialExact(
  k = 3, theta = seq(0.1, 0.9, 0.1), n.I = c(12, 24, 36),
  a = c(-1, 0, 11), b = c(5, 9, 12)
)
zz %>%
  as_table() %>%
  as_rtf(
    file = tempfile(fileext = ".rtf"),
    title = "Power/Type I Error and Expected Sample Size for a Group Sequential Design"
  )

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_rtf(
    file = tempfile(fileext = ".rtf"),
    theta_label = "Underlying\nAE Rate",
    prob_decimals = 3,
    bound_label = c("Low Rate", "High Rate")
  )
# as_rtf for gsBoundSummary
xgs <- gsSurv(lambdaC = .2, hr = .5, eta = .1, T = 2, minfup = 1.5)
gsBoundSummary(xgs, timename = "Year", tdigits = 1) %>% as_rtf(file = tempfile(fileext = ".rtf"))

ss <- nSurvival(
  lambda1 = .2, lambda2 = .1, eta = .1, Ts = 2, Tr = .5,
  sided = 1, alpha = .025, ratio = 2
)
xs <- gsDesign(nFixSurv = ss$n, n.fix = ss$nEvents, delta1 = log(ss$lambda2 / ss$lambda1))
gsBoundSummary(xs, logdelta = TRUE, ratio = ss$ratio) %>% as_rtf(file = tempfile(fileext = ".rtf"))

xs <- gsDesign(nFixSurv = ss$n, n.fix = ss$nEvents, delta1 = log(ss$lambda2 / ss$lambda1))
gsBoundSummary(xs, logdelta = TRUE, ratio = ss$ratio) %>% 
  as_rtf(file = tempfile(fileext = ".rtf"),
  footnote_specify = "Z",
  footnote_text = "Z-Score")