print.Glm

Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit.  'rms' is a collection of functions that
assist with and streamline modeling.  It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models.  'rms' works with almost any regression model, but it
was especially written to work with binary or ordinal regression
models, Cox regression, accelerated failure time models,
ordinary linear models,	the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.

Frank Harrell Jr

Regression Modeling Strategies

print.Glm function

<dl><dt>x</dt>
<dd>`Glm` object</dd>
<dt>digits</dt>
<dd>number of significant digits to print</dd>
<dt>coefs</dt>
<dd>specify `coefs=FALSE` to suppress printing the table of
model coefficients, standard errors, etc. Specify `coefs=n` to print
only the first `n` regression coefficients in the model.</dd>
<dt>title</dt>
<dd>a character string title to be passed to `prModFit`</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

print.glm — print.Glm

<dl>

<dt>x</dt>
<dd>`Glm` object</dd>


<dt>digits</dt>
<dd>number of significant digits to print</dd>


<dt>coefs</dt>
<dd>specify `coefs=FALSE` to suppress printing the table of
model coefficients, standard errors, etc. Specify `coefs=n` to print
only the first `n` regression coefficients in the model.</dd>


<dt>title</dt>
<dd>a character string title to be passed to `prModFit`</dd>


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

</dl>

print.Glm: print.glm

Description

Usage

Arguments

Author

Details