We have made the spending function summary output more readable and informative.
a b = 0.5 1.5
is now displayed as
a = 0.5, b = 1.5
(@jdblischak, #162).summary()
method for sfLDOF()
no longer includes the redundant
none = 1
in its output (@jdblischak, #159).sfupar
in sfLDOF()
to create a generalized O'Brien-Fleming spending function
(@keaven, 52cc711,
99996b).sfXG1()
, sfXG2()
,
and sfXG3()
based on Xi and Gallo (2019).
See vignette("ConditionalErrorSpending")
for details and reproduced
examples from the literature (@keaven, #147. Thanks, @xidongdxi,
for comments on vignette).eEvents()
with input validation to ensure lambda
is not NULL
(@keaven, 97f629d).gsSurvCalendar()
(@myeongjong, #144).gsBinomialExact()
(@menglu2, #143).vignette("ConditionalPowerPlot")
(beb2957,
727fe20,
57394fe).gsBoundSummary()
now has the as_rtf()
method implemented to generate
RTF outputs for bound summary tables (@wangben718, #107).plotgsPower()
gets new arguments offset
and titleAnalysisLegend
to enable more flexible and accurate power plots (plottype = 2
)
(@jdblischak, #121, #123).dplyr::reframe()
to replace
dplyr::summarize()
when performing grouped cumsum()
(@jdblischak, #114)..data
pronoun from rlang
with ggplot2::aes()
. This simplifies the code and follows the
recommended practice when using ggplot2 in packages (@jdblischak, #124).hGraph()
now uses named guide
argument in the scale_fill_manual()
call
to be compatible with ggplot2 3.5.0 (@teunbrand, #115).
Note: this function has been deprecated and moved to gMCPLite
since gsDesign 3.4.0. It will be removed from gsDesign in a future version.
Please use gMCPLite::hGraph()
instead.vignettes("SurvivalOverview")
is updated with more details and
minor corrections (@keaven, #126).gsSurv()
and nSurv()
have updated default values for T
and minfup
so that function calls with no arguments will run. Legacy code with T
or minfup
not explicitly specified could break (#105).gsSurvCalendar()
function added to enable group sequential design for
time-to-event outcomes using calendar timing of interim analysis
specification (#105).as_rtf()
method for gsBinomialExact()
objects added,
enable RTF table outputs for standard word processing software (#102).toBinomialExact()
and gsBinomialExact()
: fix error checking in bound
computations, improve documentation and error messages (#105).print.gsSurv()
: Improve the display of targeted events (very minor).
The boundary crossing probability computations did not change.
The need is made evident by the addition of the toInteger()
function (#105).toInteger()
: Fix the documentation and execution based on the ratio
argument (#105).sfPower()
now allows a wider parameter range (0, 15].toInteger()
function added to convert gsDesign
or gsSurv
classes
to integer sample size and event counts.toBinomialExact()
function added to convert time-to-event bounds to
exact binomial for low event rate studies.as_table()
and as_gt()
methods for gsBinomialExact
objects added,
as described in the new "Binomial SPRT" vignette.plot.ssrCP()
, the hat
syntax in the mathematical expression is revised,
resolving labeling issues.ggplot2::qplot()
usage replaced due to its deprecation in ggplot2 3.4.0.gsCP()
interim test statistic zi (#63).hGraph()
and suggested using gMCPLite::hGraph()
instead (#70).Depends
to Imports
(#56).inherits()
instead of is()
to determine if an object is an instance of a class, when appropriatehGraph()
to support ggplot2 versions of multiplicity graphssequentialPValue
sequentialPValue
functiongsDesign
and gsSurv
R CMD check
warningsnBinomial1Sample()
nBinomial1Sample()
to improve error handling and claritysfLDOF()
to generalize with rho parameter; still backwards compatible for Lan-DeMets O'Brien-FleminggsDesign()
function and the change is the addition of the parameters usTime
and lsTime
; default behavior is backwards compatible.gsCP()
opts()
importFrom
statements - and DESCRIPTION - adding plyr to imports) ensuring appropriate references.xtable.gsSurv
and print.gsSurv
to work with 1-sided designsshow.legend
arguments where used in ggplot2::geom_text
calls; no user impactsfLogistic
help filesfTrimmed
as likely preferred spending function approach to skipping early or all interim efficacy analyses; this also can adjust bound when final analysis is performed with less than maximum planned information. Updated help(sfTrimmed)
to demonstrate these capabilities.sfGapped
, which is primarily intended to eliminate futility analyses later in a study; see help(sfGapped)
for an examplesummary.spendfn()
to provide textual summary of spending functions; this simplified the print function for gsDesign objectssfStep()
which can be used to set an interim spend when the exact amount of information is unknown; an example of how this can be misused is provided in the help filegsBoundSummary
, xtable.gsSurv
and summary.gsDesign
are consistent for gsSurv
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