VAP_data

It is a tiny subset of the OUTCOMEREA database whose only perhaps will be to
test an illustrate the functions of this package.

Extends the test-based Bayes factor (TBF) methodology to multinomial regression models and discrete time-to-event models with competing risks. The TBF methodology has been well developed and implemented for the generalised linear model [Held et al. (2015) <doi:10.1214/14-STS510>] and for the Cox model [Held et al. (2016) <doi:10.1002/sim.7089>].

Rachel Heyard

TBFmultinomial

TBF Methodology Extension for Multinomial Outcomes

VAP_data function

A data frame with 1640 rows and 7 variables on 90 distinct patients:<dl class="dl-horizontal">
 <dt>ID</dt><dd>distinct ID for each patient</dd>
 <dt>day</dt><dd>day of ventilation, day = 1 is the first day of ventilation</dd>
 <dt>type</dt><dd>is it a medical or a surgical patient</dd>
 <dt>gender</dt><dd>gender of the patient, 1 = male, 0 = female</dd>
 <dt>SAPSadmission</dt><dd>the SAPS 2 score at admission to the ICU</dd>
 <dt>SOFA</dt><dd>the daily SOFA score</dd>
 <dt>outcome</dt><dd>final outcome after the first observation period</dd>
</dl>

Format

Data on VAP acquistion in one ICU — VAP_data

A data frame with 1640 rows and 7 variables on 90 distinct patients:<dl class='dl-horizontal'>
 <dt>ID</dt><dd>distinct ID for each patient</dd>
 <dt>day</dt><dd>day of ventilation, day = 1 is the first day of ventilation</dd>
 <dt>type</dt><dd>is it a medical or a surgical patient</dd>
 <dt>gender</dt><dd>gender of the patient, 1 = male, 0 = female</dd>
 <dt>SAPSadmission</dt><dd>the SAPS 2 score at admission to the ICU</dd>
 <dt>SOFA</dt><dd>the daily SOFA score</dd>
 <dt>outcome</dt><dd>final outcome after the first observation period</dd>
</dl>

VAP_data: Data on VAP acquistion in one ICU

Description

Usage

Arguments

Format