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2 changes: 1 addition & 1 deletion DESCRIPTION
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@@ -1,6 +1,6 @@
Package: gsDesign2
Title: Group Sequential Design with Non-Constant Effect
Version: 1.1.6.1
Version: 1.1.7
Authors@R: c(
person("Keaven", "Anderson", email = "keaven_anderson@merck.com", role = c("aut")),
person("Yujie", "Zhao", email = "yujie.zhao@merck.com", role = c("aut", "cre")),
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13 changes: 12 additions & 1 deletion NEWS.md
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@@ -1,8 +1,19 @@
# gsDesign2 1.1.7

## User interface improvements
## Documentation

- The vignette discussing the futility boundary design is finalized (#583, thanks to @LittleBeannie)
- An example calculating expected events for multiple strata is added (#597, thanks to @LittleBeannie)
- The documentation of common parameters is unified by `@inheritparams` (#598, thanks to @LittleBeannie)
- A contributing guide with overview of package architecture is added (#596, thanks to @jdblischak)

## Programming improvements

- The S3 classes are re-factored (#584, thanks to @jdblischak)
- The input parameters are not displayed when printing the objects (#586, thanks to @jdblischak)
- `text_summary()` supports design objects with spending functions specified as character strings (#587, thanks to @yihui).
- The attribute assignment `uninteger_is_from` is fixed in `to_integer()` (#591, thanks to @jdblischak)
- `text_summary()` is updated to support fixed designs from `gs_design_ahr()` (#592, thanks to @jdblischak)

# gsDesign2 1.1.6

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16 changes: 9 additions & 7 deletions R/expected_event.R
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Expand Up @@ -109,13 +109,15 @@
#' )
#'
#' # Single time period example, multiple strata
#' enroll_rate <- define_enroll_rate(stratum = rep(c("Biomarker-positive", "Biomarker-negative"), each = 4),
#' duration = c(2, 2, 2, 6, 2, 2, 2, 6),
#' rate = c(1:4, 1:4))
#' failure_rate <- define_fail_rate(stratum = rep(c("Biomarker-positive", "Biomarker-negative"), each = 2),
#' duration = c(3, 100, 3, 100),
#' fail_rate = log(2) / c(8, 12, 8, 10),
#' dropout_rate = 0.001)
#' enroll_rate <- define_enroll_rate(
#' stratum = rep(c("Biomarker-positive", "Biomarker-negative"), each = 4),
#' duration = c(2, 2, 2, 6, 2, 2, 2, 6),
#' rate = c(1:4, 1:4))
#' failure_rate <- define_fail_rate(
#' stratum = rep(c("Biomarker-positive", "Biomarker-negative"), each = 2),
#' duration = c(3, 100, 3, 100),
#' fail_rate = log(2) / c(8, 12, 8, 10),
#' dropout_rate = 0.001)
#' # Number of expected events by stratum
#' sapply(c("Biomarker-positive", "Biomarker-negative"),
#' function(ss){
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16 changes: 9 additions & 7 deletions man/expected_event.Rd

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