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.