hce 0.8.5

Added an implementation summaryWO.adhce() to provide the summaries by GROUP, as opposed to summaryWO.hce(), which works without grouping by this variable.
Details have been added regarding the implementation of the simKHCE() function. The function has been updated to return all time-to-event outcomes for each patient in the ADET dataset.
A bug has been fixed in regWO(), which previously caused the results to depend on the order of the input dataset. This issue also affected the stratWO() function, since it calls regWO(). A similar issue in the IWP() has also been fixed. The bug was reported by Cyrill Scheidegger.
The hce() function has been for consistency with the as_hce() function. Two new arguments, PADY and AVAL0, have been added. The PADY argument serves a similar purpose as now-deprecated ORD argument. With these updates, hce() can produce outputs of class adhce when the AVAL0 argument is provided.
Examples have been added to the calcWINS() implementation to illustrate the differences between the following formulas for the standard error of the win proportion: the Bamber-Brunner-Konietschke formula (see Bamber, 1975; Brunner and Konietschke, 2025), Brunner-Munzel test (Brunner and Munzel, 2000) based on the DeLong-Clarke-Pearson (1988) formula, and the Somers (1962) formula.

hce 0.8.0

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The function simADHCE() has been replaced by the all_data = TRUE implementation in simHCE().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.

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().

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).

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).

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.

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.