Package: hce 0.6.5

Samvel B. Gasparyan

hce: Design and Analysis of Hierarchical Composite Endpoints

Simulate and analyze hierarchical composite endpoints. Win odds is the main analysis method, but other win statistics (win ratio, net benefit) are also implemented, provided there is no censoring. See Gasparyan SB et al (2023) "Hierarchical Composite Endpoints in COVID-19: The DARE-19 Trial." Case Studies in Innovative Clinical Trials, 95-148. Chapman; Hall/CRC. <doi:10.1201/9781003288640-7>.

Authors:Samvel B. Gasparyan [aut, cre]

hce_0.6.5.tar.gz
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hce_0.6.5.tgz(r-4.4-emscripten)hce_0.6.5.tgz(r-4.3-emscripten)
hce.pdf |hce.html✨
hce/json (API)
NEWS

# Install 'hce' in R:
install.packages('hce', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • 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.
  • 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.
  • 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.
  • KHCE - Kidney Hierarchical Composite Endpoint dataset.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.37 score 1 packages 13 scripts 429 downloads 15 exports 0 dependencies

Last updated 1 months agofrom:f505a56537. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-linuxOKNov 16 2024

Exports:as_hcecalcWINScalcWOhceminWOpowerWOpropWINSregWOsimADHCEsimHCEsimORDsizeWOsizeWRstratWOsummaryWO

Dependencies:

Hierarchical composite endpoints

Samvel B. Gasparyan

Rendered fromhce.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2024-10-16
Started: 2023-08-17

Introduction

Samvel B. Gasparyan

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2024-10-16
Started: 2022-11-16

Visualization of HCE using maraca plots

Samvel B. Gasparyan

Rendered frommaraca.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2024-10-16
Started: 2023-10-31

Win statistics

Samvel B. Gasparyan

Rendered fromWins.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2024-10-16
Started: 2023-01-16

Readme and manuals

Help Manual

Help pageTopics
Event-Time dataset for kidney outcomes.ADET
Laboratory dataset for Glomerular Filtration Rate (GFR) measurements.ADLB
Baseline characteristics dataset of patients with kidney function assessments.ADSL
A generic function for coercing data structures to 'hce' objectsas_hce
Coerce a data frame to an 'hce' objectas_hce.data.frame
A generic function for calculating win statisticscalcWINS
Win statistics calculation using a data framecalcWINS.data.frame
Win statistics calculation using formula syntaxcalcWINS.formula
Win statistics calculation for 'hce' objectscalcWINS.hce
A generic function for calculating win oddscalcWO
Win odds calculation using a data framecalcWO.data.frame
Win odds calculation using formula syntaxcalcWO.formula
Win odds calculation for 'hce' objectscalcWO.hce
COVID-19 ordinal scale dataset (full report).COVID19
COVID-19 ordinal scale dataset (preliminary report).COVID19b
COVID-19 ordinal scale dataset for a combination therapy.COVID19plus
Helper function for 'hce' objectshce
'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.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
Kidney Hierarchical Composite Endpoint dataset.KHCE
Minimum detectable or WO for alternative hypothesis for given power (no ties)minWO
A print method for 'hce_results ' objectsplot.hce_results
Power calculation for the win odds test (no ties)powerWO
A print method for 'hce_results' objectsprint.hce_results
Proportion of wins/losses/ties given the win odds and the win ratiopropWINS
A generic function for win odds regressionregWO
Win odds regression using a data frameregWO.data.frame
Simulate 'adhce' object with given event rates of time-to-event outcomes (Weibull), mean and SD of the continuous outcome (normal or log-normal) by treatment groupsimADHCE
Simulate 'hce' object with given event rates of time-to-event outcomes (Weibull), mean and SD of the continuous outcome (normal or log-normal) by treatment groupsimHCE
Simulate ordinal variables for two treatment groups using categorization of beta distributionssimORD
Sample size calculation for the win odds test (no ties)sizeWO
Sample size calculation for the win ratio test (with WR = 1 null hypothesis)sizeWR
A generic function for stratified win odds with adjustmentstratWO
Stratified win odds with adjustmentstratWO.data.frame
A generic function for summarizing win oddssummaryWO
Win odds summary for a data framesummaryWO.data.frame
Win odds summary using formula syntaxsummaryWO.formula
Win odds summary for 'hce' objectssummaryWO.hce