This is a toy dataset to illustrate the use of the the MSCA library

Provides basic tools and wrapper functions for computing clusters of instances described by multiple time-to-event censored endpoints. From long-format datasets, where one instance is described by one or more dated records, the main function, `make_state_matrices()`, creates state matrices. Based on these matrices, optimised procedures using the Jaccard distance between instances enable the construction of longitudinal typologies. The package is under active development, with additional tools for graphical representation of typologies planned. For methodological details, see our accompanying paper: `Delord M, Douiri A (2025) <doi:10.1186/s12874-025-02476-7>`.

Marc Delord

MSCA

Unsupervised Clustering of Multiple Censored Time-to-Event
Endpoints

EHR function

A data frame with <code>3000</code> records and <code>3</code> variables:<dl>
<dt>link_id</dt>
<dd>Unique patient identifyer</dd><dt>reg</dt>
<dd>Registered long-term condition</dd><dt>aos</dt>
<dd>Age at onset of the registered long-term condition</dd></dl>

Format

Description of the EHR dataset — EHR

A data frame with <code>3000</code> records and <code>3</code> variables:<dl>
<dt>link_id</dt>
<dd>Unique patient identifyer</dd>

<dt>reg</dt>
<dd>Registered long-term condition</dd>

<dt>aos</dt>
<dd>Age at onset of the registered long-term condition</dd>



</dl>

EHR: Description of the EHR dataset

Description

Arguments

Format

Examples