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CMFsurrogate  

Calibrated Model Fusion Approach to Combine Surrogate Markers
View on CRAN: Click here


Download and install CMFsurrogate package within the R console
Install from CRAN:
install.packages("CMFsurrogate")

Install from Github:
library("remotes")
install_github("cran/CMFsurrogate")

Install by package version:
library("remotes")
install_version("CMFsurrogate", "1.0")



Attach the package and use:
library("CMFsurrogate")
Maintained by
Layla Parast
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-23
Latest Update: 2022-09-23
Description:
Uses a calibrated model fusion approach to optimally combine multiple surrogate markers. Specifically, two initial estimates of optimal composite scores of the markers are obtained; the optimal calibrated combination of the two estimated scores is then constructed which ensures both validity of the final combined score and optimality with respect to the proportion of treatment effect explained (PTE) by the final combined score. The primary function, pte.estimate.multiple(), estimates the PTE of the identified combination of multiple surrogate markers. Details are described in Wang et al (2022) .
How to cite:
Layla Parast (2022). CMFsurrogate: Calibrated Model Fusion Approach to Combine Surrogate Markers. R package version 1.0, https://cran.r-project.org/web/packages/CMFsurrogate. Accessed 21 Nov. 2024.
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Complete documentation for CMFsurrogate
Functions, R codes and Examples using the CMFsurrogate R package
Some associated functions: example.data . gen.bootstrap.weights . pte.estimate.multiple . resam . 
Some associated R codes: funs.R .  Full CMFsurrogate package functions and examples
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