Category: data management
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
Understanding the longitudinal data workflow: a comprehensive guide
Unlock insights from longitudinal data with our step-by-step guide, from import to analysis. Master the workflow to elevate your research. Read more
Complete guide to visualizing longitudinal data in R
Unlock the secrets of longitudinal data in R with this complete guide. Master the art of insightful visualizations for impactful analysis. Read more
Exploring longitudinal data in R: tables and summaries
Unlock the power of R for longitudinal data analysis! Learn to navigate tables and summaries with ease in our latest guide. Read more
Cleaning longitudinal data in R: a step-by-step guide
Explore key R commands for cleaning longitudinal data, including recoding variables and handling missing data effectively. Read more
Preparing longitudinal data for analysis in R: a step-by-step guide
Explore the crucial steps of data preparation for longitudinal analysis in R, from importing to reshaping data, in this step-by-step guide. Read more
Data structures for longitudinal analysis: wide versus long
Learn how to create, store and reshape longitudinal data. Reshaping data from wide to long data format and back using R. Hands on examples Read more