hce 0.7.5
- Fixed a bug in
summaryWO.formula()
that previously
caused errors when GROUP
values were used.
- The function
simADHCE()
has been replaced by the
all_data = TRUE
implementation in
simHCE()
.
- The function
simHCE()
now returns an object of a new
class called adhce
. This class inherits from the
hce
class, which itself is a subclass of
data.frame
. The underlying structure of the returned object
remains unchanged. The introduction of the adhce
class is
intended to clearly distinguish these structured outputs from the more
general hce
objects. Specifically, an adhce
object is an analysis-ready hce
object that is derived
using multiple time-to-event outcomes and a single continuous (ordinal
or score) endpoint.
- The function
as_hce()
has been updated to support
additional output flexibility. If the input data includes the variables
TRTP
, GROUP
, AVAL0
, and
PADY
, the function will return an adhce
object. In this scenario, even if the AVAL
variable is
present, it will be recalculated based on the provided data to ensure
consistency with the adhce
structure. If only the
TRTP
and AVAL
variables are available,
as_hce()
will return a standard hce
object.
This enhancement allows users to generate either general or
analysis-ready hce
objects, depending on the available
input variables.
hce 0.7.2
regWO()
and stratWO()
are updated to
return the confidence interval for the adjusted and stratified (or
adjusted/stratified) win probability as well.
- Added the formula implementation of
regWO().
hce 0.7.0
plot()
method for hce
objects (created by
the function as_hce()
) is updated to include a
fill
argument for filling the area above the graph.
calcWINS()
is updated to include the
SE_WP_Type
argument with default "biased"
(original implementation) and a new "unbiased"
implementation of the Bamber-Brunner-Konietschke (see Bamber (1975),
Brunner and Konietschke (2025)) standard error for the win
proportion.
- New function
IWP()
is added to calculated patient-level
individual win proportions.
- Default method for the generic
as_hce()
is added.
- The vignette on hierarchical composite endpoints is updated to
include the theoretical framework for the simulation of dependent
outcomes using the given copula.
- The function
simHCE()
is updated to correct for the
copula implementation so that theta = 1
(case of
independence) and theta
close to 1 now give similar results
(as expected).
hce 0.6.7
- The function
simHCE()
is updated to include a new
theta
argument for Gumbel dependence coefficient of the
Weibull distributions for time-to-event outcomes. Default is
theta = 1
which assumes independence of time-to-event
outcomes. The argument is still experimental.
calcWO()
is updated to return the confidence interval
for the win probability as well.
plot()
method for hce
objects (created by
the function as_hce()
) is implemented to provide the
ordinal dominance graph as suggested by Bamber (1975).
hce 0.6.5
- The functions
powerWO(), sizeWO(), minWO()
are updated
to include a new argument alternative
to specify the class
of alternative hypothesis. All formulas are based on the Bamber (1975)
paper.
- Added a new dataset
COVID19plus.
hce 0.6.3
- Added a
NEWS.md
file to track changes to the
package.
- The hex sticker of the package has been created and is included in
all vignettes.
HCE1 - HCE4
datasest are updated to follow the standard
structure.
- A new argument
dec
is added to simHCE()
for decimal places used for rounding the continuous outcome in the
simulated dataset. Additionally, the default value for the standard
deviation of the continuous variable in the placebo group
CSD_P
is changed to be equal to that of the active group
CSD_A
instead of being equal to 1.
- A new function
simADHCE()
which simulates
adhce
objects, that is, an hce
object with its
source datasets. Works similar to simHCE()
which provides
only an hce
object.
- A new function
simORD()
which simulates ordinal
endpoint by categorizing beta distributions.