# Design and Analysis of Hierarchical Composite Endpoints

## Documentation for package ‘hce’ version 0.9.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

ADET | Event-Time dataset for kidney outcomes.
ADLB | Laboratory dataset for Glomerular Filtration Rate (GFR) measurements.
ADSL | Baseline characteristics dataset of patients with kidney function assessments.
as_formulae | Decompose formula objects
as_formulae.formula | Decompose formula objects
as_hce | A generic function for coercing data structures to 'hce' objects
as_hce.data.frame | Coerce a data frame to an 'hce' object
as_hce.default | Coerce a data frame to an 'hce' object
calcWINS | A generic function for calculating win statistics
calcWINS.data.frame | Win statistics calculation using a data frame
calcWINS.formula | Win statistics calculation using formula syntax
calcWINS.hce | Win statistics calculation for 'hce' objects
calcWO | A generic function for calculating win odds
calcWO.data.frame | Win odds calculation using a data frame
calcWO.formula | Win odds calculation using formula syntax
calcWO.hce | Win odds calculation for 'hce' objects
COVID19 | COVID-19 ordinal scale dataset (full report).
COVID19b | COVID-19 ordinal scale dataset (preliminary report).
COVID19plus | COVID-19 ordinal scale dataset for a combination therapy.
deltaWO | A generic function for calculating win odds based on a threshold
deltaWO.adhce | Win odds calculation based on a threshold for 'adhce' objects
dGLL | The Generalized Log-Logistic Distribution
formulae | Decompose formula objects
GLL | The Generalized Log-Logistic Distribution
hce | Helper function for 'hce' objects
HCE1 | 'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
HCE2 | 'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
HCE3 | 'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
HCE4 | 'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.
HGLL | The Generalized Log-Logistic Distribution
hGLL | The Generalized Log-Logistic Distribution
IWP | Calculates patient-level individual win proportions
KHCE | Kidney Hierarchical Composite Endpoint dataset.
minWO | Minimum detectable or WO for alternative hypothesis for given power (no ties)
pGLL | The Generalized Log-Logistic Distribution
plot.hce | A plot method for 'hce' objects
plot.hce_results | A print method for 'hce_results ' objects
powerWO | Power calculation for the win odds test (no ties)
print.hce_results | A print method for 'hce_results' objects
propWINS | Proportion of wins/losses/ties given the win odds and the win ratio
qGLL | The Generalized Log-Logistic Distribution
regWO | A generic function for win odds regression
regWO.data.frame | Win Odds Regression Using a Data Frame
regWO.formula | Win Odds Regression Using a Formula Syntax
rGLL | The Generalized Log-Logistic Distribution
rweibullGF | Simulate random numbers from a Weibull distribution with gamma frailty
simHCE | Simulate an 'hce' object
simKHCE | Simulate a kidney disease 'hce' dataset
simORD | Simulate ordinal variables for two treatment groups using categorization of beta distributions
simTTE | Simulate an 'adhce' dataset with two correlated outcomes (illness - death model)
sizeWO | Sample size calculation for the win odds test (no ties)
sizeWR | Sample size calculation for the win ratio test (with WR = 1 null hypothesis)
stratWO | A generic function for stratified win odds with adjustment
stratWO.data.frame | Stratified win odds with adjustment
stratWO.formula | Stratified win odds with adjustment using formula
summaryWO | A generic function for summarizing win odds
summaryWO.adhce | Win odds summary for 'adhce' objects
summaryWO.data.frame | Win odds summary for a data frame
summaryWO.formula | Win odds summary using formula syntax
summaryWO.hce | Win odds summary for 'hce' objects