BuyseTest (version 3.0.5)

S4BuyseTest-model.tables: Extract Summary for Class "S4BuyseTest"

Description

Extract a summary of the results from the BuyseTest function.

Usage

# S4 method for S4BuyseTest
model.tables(
  x,
  percentage = TRUE,
  statistic = NULL,
  conf.level = NULL,
  strata = NULL,
  columns = "summary",
  ...
)

Arguments

x

output of BuyseTest

percentage

[logical] Should the percentage of pairs of each type be displayed ? Otherwise the number of pairs is displayed.

statistic

[character] the statistic summarizing the pairwise comparison: "netBenefit" displays the net benefit, as described in Buyse (2010) and Peron et al. (2016)), "winRatio" displays the win ratio, as described in Wang et al. (2016), "favorable" displays the proportion in favor of the treatment (also called Mann-Whitney parameter), as described in Fay et al. (2018). "unfavorable" displays the proportion in favor of the control. Default value read from BuyseTest.options().

conf.level

[numeric] confidence level for the confidence intervals. Default value read from BuyseTest.options().

strata

[logical] should the strata-specific results be displayed or the results pooled across strata? Can also be NULL to display both.

columns

[character vector] subset of columns to be output (e.g. "endpoint", "favorable", ...). Can also be "summary" or "print" to only select columns displayed in the summary or print. NULL will select all columns.

...

arguments to be passed to S4BuyseTest-confint

Author

Brice Ozenne

See Also

BuyseTest for performing a generalized pairwise comparison.
S4BuyseTest-class for a presentation of the S4BuyseTest object.
S4BuyseTest-confint to output confidence interval and p-values in a matrix format.

Examples

library(data.table)

dt <- simBuyseTest(1e2, n.strata = 3)

 if (FALSE) {
 BT <- BuyseTest(treatment ~ TTE(eventtime, status = status) + Bin(toxicity), data=dt)
 }
 # \dontshow{
 BT <- BuyseTest(treatment ~ TTE(eventtime, status = status) + Bin(toxicity), data=dt, n.resampling = 10, trace = 0)
 # }
 model.tables(BT)
 model.tables(BT, percentage = FALSE)
 model.tables(BT, statistic = "winRatio")