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bhm (version 1.19)

Biomarker Threshold Models

Description

Contains tools to fit both predictive and prognostic biomarker effects using biomarker threshold models and continuous threshold models. Evaluate the treatment effect, biomarker effect and treatment-biomarker interaction using probability index measurement. Test for treatment-biomarker interaction using residual bootstrap method.

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Version

Install

install.packages('bhm')

Monthly Downloads

310

Version

1.19

License

GPL (>= 2)

Maintainer

Bingshu Chen

Last Published

April 26th, 2025

Functions in bhm (1.19)

data

dataset
bhmControl

Auxiliary function for bhm fitting
bhm-package

An R package for the biomarker threshold models
ars

Function to perform Adaptive Rejection Sampling
numScore

Calculate the Score / Jacobian Function
resboot

Rresidual Bootstrap Test (RBT) for treatment-biomarker interaction
multiRoot

m-Dimensional Root (Zero) Finding
numHessian

Calculate Hessian or Information Matrix
pIndexControl

Auxiliary function for pIndex fitting
rpicexp

The Piecewise Exponential Distribution
plot

Plot a fitted biomarker threhold model
rmscb

Fitting Restricted Mean Survival Time Models with a Continuous Biomarker
pIndex

Probability Index for Survival Time Difference
print

print a fitted object or a summary of fitted object
ggkm

Creates a Kaplan-Meier plot with at risk tables below
bhm

Fitting Biomarker Threshold Models
glmpLRT

Penalized likelihood ratio test for the generalized linear models.
brm

Fitting Biomarker Continuous Threshold Models
mpl

Joint models for clustered data with binary and survival outcomes.
llm

Fit an L-shape linear model