survest.orm

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

survest.orm function

<dl><dt>fit</dt>
<dd>result of <code>orm</code></dd>
<dt>newdata</dt>
<dd>data frame defining covariate settings</dd>
<dt>linear.predictors</dt>
<dd>linear predictor vector using the reference intercept</dd>
<dt>x</dt>
<dd>design matrix</dd>
<dt>times</dt>
<dd>times for which estimates are desired; defaults to estimating probabilities of T &gt; t for all uncensored times</dd>
<dt>fun</dt>
<dd>optional transformation of survival probabilities</dd>
<dt>loglog</dt>
<dd>set to <code>TRUE</code> to use the log-log transformatino</dd>
<dt>conf.int</dt>
<dd>a number between 0-1 with the default of 0.95; set to 0 to not compute CLs</dd>
<dt>what</dt>
<dd>specify <code>what='parallel'</code> to compute the survival probability at the observed linear predictor and time values, both varying; all possible combinations of these are then not created</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

Title survest.orm — survest.orm

<dl>

<dt>fit</dt>
<dd>result of <code>orm</code></dd>


<dt>newdata</dt>
<dd>data frame defining covariate settings</dd>


<dt>linear.predictors</dt>
<dd>linear predictor vector using the reference intercept</dd>


<dt>x</dt>
<dd>design matrix</dd>


<dt>times</dt>
<dd>times for which estimates are desired; defaults to estimating probabilities of T &gt; t for all uncensored times</dd>


<dt>fun</dt>
<dd>optional transformation of survival probabilities</dd>


<dt>loglog</dt>
<dd>set to <code>TRUE</code> to use the log-log transformatino</dd>


<dt>conf.int</dt>
<dd>a number between 0-1 with the default of 0.95; set to 0 to not compute CLs</dd>


<dt>what</dt>
<dd>specify <code>what='parallel'</code> to compute the survival probability at the observed linear predictor and time values, both varying; all possible combinations of these are then not created</dd>


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

</dl>

survest.orm: Title survest.orm

Description

Usage

Value

Arguments

Author

Examples