print.predict.blrm

Prints the summary portion of the results of <code>predict.blrm</code>

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>.

Frank Harrell Jr

rmsb

Bayesian Regression Modeling Strategies

Frank Harrell

Ben Goodrich

Ben Bolker

Doug Bates

print.predict.blrm function

<dl><dt>x</dt>
<dd>result from <code>predict.blrm</code></dd>
<dt>digits</dt>
<dd>number of digits to round numeric results</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

Print Predictions for blrm() — print.predict.blrm

<dl>

<dt>x</dt>
<dd>result from <code>predict.blrm</code></dd>


<dt>digits</dt>
<dd>number of digits to round numeric results</dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

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print.predict.blrm: Print Predictions for `blrm()`

Description

Usage

Arguments

Author