Longitudinal data

Latent Class Growth Analysis

• Groups individuals into distinct trajectory classes over time.

• Individuals in the same class follow a similar longitudinal pattern.

• No within-class variance (trajectories are homogeneous within each class).

• Clear, discrete groups of longitudinal patterns.

• https://www.statisticalinnovations.com/wp-content/uploads/Magidson\_2020\_LatentClassAnalysis.pdf ## Growth Mixture Modeling (GMM)

Hidden Markov Models (HMMs)

• Individuals transition between latent states over time
• Focus is on state switching, not stable trajectory groups
• Good for behavioral or clinical state changes

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