getUnivariableSeparability

<code>getUnivariableSeparability</code> reports covariates that are univariably separable with the outcome

This model fitting tool incorporates cyclic coordinate descent and
majorization-minimization approaches to fit a variety of regression models
found in large-scale observational healthcare data. Implementations focus
on computational optimization and fine-scale parallelization to yield
efficient inference in massive datasets. Please see:
Suchard, Simpson, Zorych, Ryan and Madigan (2013) <doi:10.1145/2414416.2414791>.

Marc A Suchard

Cyclops

Cyclic Coordinate Descent for Logistic, Poisson and Survival
Analysis

Marc A. Suchard

Martijn J. Schuemie

Trevor R. Shaddox

Yuxi Tian

Jianxiao Yang

Eric Kawaguchi

Sushil Mittal

Observational Health Data Sciences and Informatics 

Marcus Geelnard

Rutgers University 

R Development Core Team 

getUnivariableSeparability function

<dl><dt>cyclopsData</dt>
<dd>A Cyclops data object</dd>
<dt>covariates</dt>
<dd>Integer or string vector: list of covariates to report; default (NULL) implies all covariates</dd></dl>

Arguments

Get univariable linear separability — getUnivariableSeparability

<dl>

<dt>cyclopsData</dt>
<dd>A Cyclops data object</dd>


<dt>covariates</dt>
<dd>Integer or string vector: list of covariates to report; default (NULL) implies all covariates</dd>

</dl>

Get univariable linear separability

getUnivariableSeparability: Get univariable linear separability

Description

Usage

Value

Arguments