A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group.
|Author||Wai-ki Yip, with contributions from Ann Lazar, David Zahrieh, Chip Cole, Ann Lazar, Marco Bonetti, Victoria Wang, William Barcella and Richard Gelber|
|Date of publication||2014-10-22 09:03:30|
|Maintainer||Wai-ki Yip <firstname.lastname@example.org>|
|License||GPL (>= 2)|
analyze.CumInc.stepp: analyze competing risks data using Cumulative Incidence...
analyze.KM.stepp: analyze survival data using Kaplan-Maier method
aspirin: the aspirin data set.
big: the big data set.
estimate: the standard generic function for all estimate methods
generate: the standard generic function for the generate method in...
stepp: analyze survival or competing risks data
stepp.CI: a method to create the stmodelCI object
stepp.COX: a method to create the stmodelCOX object
steppes-class: Class '"steppes"'
stepp.GLM: a method to create the stmodelGLM object
stepp.KM: a method to create the stmodelKM object
stepp_plot: generating the stepp plots
stepp_print: a method to print the estimate, covariance matrices and test...
stepp.subpop: a method to create the stsubpop object and generate the...
stepp_summary: produce a summary of the size and various attributes of each...
stepp.test: a method to generate a complete steppes object with effect...
stepp.win: a method to create the stepp window object
stmodelCI-class: Class '"stmodelCI"'
stmodel-class: Class '"stmodel"'
stmodelCOX-class: Class '"stmodelCOX"'
stmodelGLM-class: Class '"stmodelGLM"'
stmodelKM-class: Class '"stmodelKM"'
stsubpop-class: Class '"stsubpop"'
stwin-class: Class '"stwin"'
test: the standard generic function for all test methods