checkEventExposureIndependenceAssumption

This diagnostic tests whether there is a dependency between the event and subsequent exposures.
This requires you have indicated one of the era covariates to be a pre-exposure window. This
function simply checks whether the confidence interval for the effect estimate of that pre-
exposure window overlaps with the <code>nullBounds</code>.
To designate an era covariate to be the pre-exposure window, set <code>preExposure = TRUE</code> when
calling <code>createEraCovariateSettings()</code>. Note that, by default, <code>preExposure</code> will be <code>TRUE</code> if
<code>start</code> is smaller than 0.

Execute the self-controlled case series (SCCS) design using observational
data in the OMOP Common Data Model. Extracts all necessary data from the database and
transforms it to the format required for SCCS. Age and season can be modeled
using splines assuming constant hazard within calendar months. Event-dependent
censoring of the observation period can be corrected for. Many exposures can be
included at once (MSCCS), with regularization on all coefficients except for the
exposure of interest. Includes diagnostics for all major assumptions of the SCCS.

Martijn Schuemie

SelfControlledCaseSeries

Self-Controlled Case Series

Patrick Ryan

Trevor Shaddox

Marc Suchard

checkEventExposureIndependenceAssumption function

<dl><dt>sccsModel</dt>
<dd>A fitted SCCS model as created using <code>fitSccsModel()</code>.</dd>
<dt>nullBounds</dt>
<dd>The bounds for the null hypothesis on the incidence rate ratio scale.</dd></dl>

Arguments

Check diagnostic for event-dependent exposure — checkEventExposureIndependenceAssumption

<dl>

<dt>sccsModel</dt>
<dd>A fitted SCCS model as created using <code>fitSccsModel()</code>.</dd>


<dt>nullBounds</dt>
<dd>The bounds for the null hypothesis on the incidence rate ratio scale.</dd>

</dl>

checkEventExposureIndependenceAssumption: Check diagnostic for event-dependent exposure

Description

Usage

Value

Arguments