Longitudinal Growth Curve Modeling

Overview

Fit growth curve models to temporal activity metadata to track a user's evolution through stages of Digital Maturity (Lurker, Participant, Community Leader/Moderator). The core principle: activity trajectories are not linear -- fit multiple candidate models, use information criteria to select the best, and detect change points that mark stage transitions rather than assuming smooth progression.

When to Use

• Temporal activity data spanning months or years (timestamps on posts, comments, votes, moderation actions)
• Need to classify a user's current Digital Maturity stage based on trajectory shape
• Investigating whether a user transitioned between participation modes (lurking to active, active to leadership)
• Comparing growth models (linear, logistic, piecewise) to find best trajectory fit
• Detecting inflection points or change points in activity rate over time
• Feeding trajectory shape into downstream persona or archetype analysis