sdata

Simulated irregular longitudinal data for 1000 patients.
This dataset contains irregularly spaced time points and responses for analysis.

datasets

Convert irregularly spaced longitudinal data into regular intervals for further analysis,
and perform clustering using advanced machine learning techniques.
The package is designed for handling complex longitudinal datasets,
optimizing them for research in healthcare, demography, and other fields
requiring temporal data modeling.

Atanu Bhattacharjee

ILRCM

Convert Irregular Longitudinal Data to Regular Intervals and
Perform Clustering

Tanmoy  Majumdar

Gajendra  Kumar Vishwakarma

sdata function

A data frame with 8631 rows and 3 variables:<dl>
 <dt>subject_id</dt>
<dd>ID of subjects</dd> <dt>time</dt>
<dd>Irregular time points.</dd> <dt>response</dt>
<dd>Response values at different time points.</dd>
</dl>

Format

Simulated Irregular Longitudinal Data — sdata

A data frame with 8631 rows and 3 variables:<dl>
 <dt>subject_id</dt>
<dd>ID of subjects</dd>

 <dt>time</dt>
<dd>Irregular time points.</dd>

 <dt>response</dt>
<dd>Response values at different time points.</dd>


</dl>

sdata: Simulated Irregular Longitudinal Data

Description

Usage

Arguments

Format

Examples