Tag: structural equation modelling
How to estimate and interpret parallel Latent Growth Models (LGM) in R: a step-by-step guide
Learn how to estimate and interpret Parallel Latent Growth Models (LGM) in R and lavaan. This step-by-step guide explores modeling multiple trajectories, analyzing relationships over time, and visualizing results. Perfect for researchers in psychology, sociology, and public health using longitudinal data. Read more
How to include time-varying predictors in Latent Growth Models (LGM) in R
This post explores how to incorporate time-varying predictors into Latent Growth Models (LGM) to analyse changes in variables over time. It discusses data preparation, using R code for modeling, and differentiating between concurrent and lagged effects. Read more
Including time constant controls in Latent Growth Models
This post discusses incorporating time-constant predictors in Latent Growth Models (LGM) using R to better understand changes over time. It details coding in R using real data. It compares strategies for including these predictors and interpreting their effects on intercept and slope in LGMs. Read more
Comparing the multilevel model with the Latent Growth Model
Learn how the multilevel model for change and the latent growth models are different and when to use each one. Hands on example using real data and R Read more
Understanding causal direction using the cross-lagged model
Learn how to investigate the causal direction of two variables using the cross-lagged model and longitudinal data. Hands on example using R and real data Read more
Estimating and visualizing Latent Growth Models with R
Tutorial showing you how to visualize change in time and how to estimate it using Latent Growth Modelling with R. Hands on longitudinal data analysis. Read more