Longitudinal Data Analysis

1 Approaches for Modeling Longitudinal Data

• Growth curve model
• Latent growth curve model
• Latent change score model
• Cross-lagged panel model

2 Estimating Nonlinear Growth

There are a variety of ways to estimate nonlinear growth in a growth curve model using a mixed-effects or structural equation model:

• polynomial growth model
  • fractional polynomial model (more parsimonious than traditional polynomials because can capture nonlinear growth with fewer parameters, thus reducing overfitting)
• piecewise/spline model
  • can have fixed or random knots
  • location of knots can be estimated for the data
  • each individual can have a different numbers of knots and different location for the knots
• latent basis growth model
  • can specify the rate of change between T1 and T2 to be one; can allow the rate of change to freely vary between remaining timepoints
• exponential growth model
• logistic growth model
• logarithmic growth model
• generalized additive model
• nonparametric growth model (e.g., kernel smoothing)
• Gompertz growth model
• Richards growth model
• Taylor series approximation model

---

---