Detecting Influential Subjects in Longitudinal Data

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.


Reference manual

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install.packages("Inflongitudinal")

0.1.0 by Tanmoy Majumdar, 8 months ago


Browse source code at https://github.com/cran/Inflongitudinal


Authors: Atanu Bhattacharjee [aut] , Tanmoy Majumdar [aut, cre] , Gajendra Kumar Vishwakarma [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports ggplot2, dplyr, mice


See at CRAN