rmsb-package

rmsb

Regression Modeling Strategies Bayesian
The rmsb package is an appendage to the rms package that
implements Bayesian regression models whose fit objects can be processed
by rms functions such as <code>contrast, summary, Predict, nomogram</code>,
and <code>latex</code>. The fitting function
currently implemented in the package is <code>blrm</code> for Bayesian logistic
binary and ordinal regression with optional clustering, censoring, and
departures from the proportional odds assumption using the partial
proportional odds model of Peterson and Harrell (1990).

A Bayesian companion to the 'rms' package, 'rmsb' provides Bayesian model fitting, post-fit estimation, and graphics. It implements Bayesian regression models whose fit objects can be processed by 'rms' functions such as 'contrast()', 'summary()', 'Predict()', 'nomogram()', and 'latex()'. The fitting function currently implemented in the package is 'blrm()' for Bayesian logistic binary and ordinal regression with optional clustering, censoring, and departures from the proportional odds assumption using the partial proportional odds model of Peterson and Harrell (1990) <https://www.jstor.org/stable/2347760>.

rmsb-package: The 'rmsb' package.

Description

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See Also