infsdata

This dataset consists of 10000 subjects with irregular observation times and influential observations.

datasets

Provides methods for detecting influential subjects in
longitudinal data, particularly when observations are collected at
irregular time points. The package identifies subjects whose response
trajectories deviate substantially from population-level patterns,
helping to diagnose anomalies and undue influence on model estimates.

Tanmoy Majumdar

Inflongitudinal

Detecting Influential Subjects in Longitudinal Data

Atanu Bhattacharjee

Gajendra Kumar Vishwakarma

infsdata function

A data frame contains:<dl>
 <dt>subject_id</dt>
<dd>Unique identifier for each subject</dd> <dt>time</dt>
<dd>Time points of observation</dd> <dt>response</dt>
<dd>Simulated response value</dd> <dt>subject_type</dt>
<dd>Category of subject (e.g., Influential, Non-Influential)</dd>
</dl>

Format

Simulated Longitudinal Data — infsdata

A data frame contains:<dl>
 <dt>subject_id</dt>
<dd>Unique identifier for each subject</dd>

 <dt>time</dt>
<dd>Time points of observation</dd>

 <dt>response</dt>
<dd>Simulated response value</dd>

 <dt>subject_type</dt>
<dd>Category of subject (e.g., Influential, Non-Influential)</dd>


</dl>

infsdata: Simulated Longitudinal Data

Description

Usage

Arguments

Format