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anoint (version 1.5)

Analysis of Interactions

Description

The tools in this package are intended to help researchers assess multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial. The methods implemented in the package were proposed in Kovalchik, Varadhan and Weiss (2013) .

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Version

Install

install.packages('anoint')

Monthly Downloads

353

Version

1.5

License

GPL (>= 2)

Maintainer

Ravi Varadhan

Last Published

September 9th, 2024

Functions in anoint (1.5)

formula.anoint-class

Class "formula.anoint"
forest

Construct a forestplot from a anoint object
anoint

Create analysis of interactions object
data.anoint

Generate a clinical trial data set under a specified multiple interaction model
pim.subsets

Perform all subsets proportional interactions modeling
print

Print coefficients of pim
plot

Prognostic response plot (PR-plot) for anoint class.
confint

Compute confindence intervals of pim model terms.
predict

Get risk predictions for pim object.
obo

Perform one-by-one (OBO) estimates of treatment-covariate interaction
anoint.subgroups

Perform one-by-one subgroup analyses
pim

Fit proportional interaction model
forest.subsets

Subsets forest plot for proportional interactions models
show.formula.anoint

Show formula.anoint object
fits

Extract fits from anoint.fit object
vcov

Get variance-covariance from pim object.
show-anoint.fit

Show table of LRT global test results for anoint.fit object
simsolvd

Simulated SOLVD-Trial data set
show.anoint

Show anoint object
pim-class

Class "pim"
coef

Get coefs from pim object.
pim.fit

Fit proportional interactions model
prognostic.score

Prognostic scores for pim object.
anoint.fit

Fits and global tests of analysis of interaction models
uim

Perform unrestricted multiple treatment-covariate interaction regression
summary

Summary of anoint model fit.
anoint.formula

Create a formula.anoint object
show

Show coefficients of pim
anoint-package

Analysis of interactions for generalized linear models (GLM) or Cox proportional hazards regression models.