20260130 - quadratic natural log transformed predictor

Author: isaactpetersen

lda.qmd

@@ -16,7 +16,7 @@ title: "Longitudinal Data Analysis"
 
 # Estimating Nonlinear Growth {#sec-nonlinear}
 
-There are a variety of ways to estimate nonlinear growth in a growth curve model using a mixed-effects or structural equation model:
+There are a variety of ways to estimate nonlinear growth in a growth curve model using a [mixed-effects](hlm.qmd) or [structural equation model](sem.qmd):
 
 - polynomial growth model
   - fractional polynomial model (more parsimonious than traditional polynomials because can capture nonlinear growth with fewer parameters, thus reducing overfitting)
@@ -29,6 +29,7 @@ There are a variety of ways to estimate nonlinear growth in a growth curve model
 - exponential growth model
 - logistic growth model
 - logarithmic growth model
+  - e.g., "an exponential pattern of change—in which change appears to 'level off' over time—can be approximated through linear (and potentially quadratic) slopes for a natural-log-transformed" version of time in a [mixed-effects model](hlm.qmd) or by fixing the latent change factor loadings to these values in [SEM](sem.qmd) (Hoffman, 2025)
 - generalized additive model
 - nonparametric growth model (e.g., kernel smoothing)
 - Gompertz growth model