data_PV

Simple simulated data, used to demonstrate the features of
functions from adapt4cv package.

datasets

A collection of several pharmacovigilance signal detection methods based on adaptive lasso. Additional lasso-based and propensity score-based signal detection approaches are also supplied. See Courtois et al <doi:10.1186/s12874-021-01450-3>.

Emeline Courtois

adapt4pv

Adaptive Approaches for Signal Detection in Pharmacovigilance

Ismaïl Ahmed

Hervé Perdry

data_PV function

<dl>
<dt>X</dt>
<dd>large sparse and binary matrix with 117160 rows and 300 columns.
Drug matrix exposure: each row corresponds to an individual and
each column corresponds to a drug.</dd><dt>Y</dt>
<dd>large spase and binary vector of length 117160. Indicator of
the presence/absence of an adverse event for ech individual.
Only the first 30 drugs (out of the 300)
are associated with the outcome.</dd>
</dl>

Format

Simulated data for the adapt4pv package — data_PV

<dl>
<dt>X</dt>
<dd>large sparse and binary matrix with 117160 rows and 300 columns.
Drug matrix exposure: each row corresponds to an individual and
each column corresponds to a drug.</dd>

<dt>Y</dt>
<dd>large spase and binary vector of length 117160. Indicator of
the presence/absence of an adverse event for ech individual.
Only the first 30 drugs (out of the 300)
are associated with the outcome.</dd>


</dl>

data_PV: Simulated data for the adapt4pv package

Description

Arguments

Format

Examples