oxford

A dataset containing the MMR vaccination / meningitis in Oxford example from
Farrington and Whitaker. There are 10 patients comprising 38 unique exposure intervals.

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 

oxford function

A data frame with 38 rows and 6 variables:<dl>
<dt>indiv</dt>
<dd>patient identifier</dd><dt>event</dt>
<dd>number of events in interval</dd><dt>interval</dt>
<dd>interval length in days</dd><dt>agegr</dt>
<dd>age group</dd><dt>exgr</dt>
<dd>exposure group</dd><dt>loginterval</dt>
<dd>log interval length</dd>...</dl>

Format

Oxford self-controlled case series data — oxford

A data frame with 38 rows and 6 variables:<dl>
<dt>indiv</dt>
<dd>patient identifier</dd>

<dt>event</dt>
<dd>number of events in interval</dd>

<dt>interval</dt>
<dd>interval length in days</dd>

<dt>agegr</dt>
<dd>age group</dd>

<dt>exgr</dt>
<dd>exposure group</dd>

<dt>loginterval</dt>
<dd>log interval length</dd>

...

</dl>

Oxford self-controlled case series data

oxford: Oxford self-controlled case series data

Description

Usage

Arguments

Format