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stepp (version 3.2.6)

Subpopulation Treatment Effect Pattern Plot (STEPP)

Description

A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two or more treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group.

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Version

Install

install.packages('stepp')

Monthly Downloads

602

Version

3.2.6

License

GPL (>= 2)

Maintainer

Wai-ki Yip

Last Published

December 18th, 2023

Functions in stepp (3.2.6)

stepp

Analyze survival or competing risks data
stepp.GLM

The constructor to create the stmodelGLM object
stepp.test

The constructor to generate a complete steppes object with effect estimates and test statistics
stepp.win

The constructor to create the stepp window object
stepp.KM

The constructor to create the stmodelKM object
stepp.rnote

The method to print the release note for STEPP.
stepp.CI

The constructor to create the stmodelCI object
stepp.edge

The method performs an edge analysis on the STEPP GLM model estimate objects.
simdataKM

Simulated data for Kaplan-Meier STEPP analysis.
stepp.subpop

The constructor to create the stsubpop object and generate the subpopulations based on the specified stepp window and covariate of interest
stmodelCI-class

Class "stmodelCI"
stepp_plot

A function to generate the stepp plots
stepp_print

The function to print the estimate, covariance matrices and test statistics.
stmodel-class

Class "stmodel"
stsubpop-class

Class "stsubpop"
stepp_summary

The function to produce a summary of the size and various attributes of each subpopulation
stmodelKM-class

Class "stmodelKM"
stmodelGLM-class

Class "stmodelGLM"
test

the standard generic function for all test methods
stwin-class

Class "stwin"
steppes-class

Class "steppes"
generate

The standard generic function for the generate method in stsubpop class
balance_patients

Utility function for determining the optimal values for generating the subpopulations.
gen.tailwin

Utility function to generate tail-oriented window
estimate

The standard generic function for all estimate methods
bigCI

The BIG 1-98 trial dataset for cumulative incidence STEPP.
analyze.KM.stepp

Analyze survival data using Kaplan-Meier method
analyze.CumInc.stepp

Analyze competing risks data using Cumulative Incidence method
balance_example

Sample data to use with the balance_patients() function.
bigKM

The BIG 1-98 trial dataset for Kaplan-Meier STEPP.
aspirin

The aspirin data set.