Hi everyone,
I would like to know how do you conduct EDA on a longitudinal study. For example, If I want to study the impact of pred1 (categorical - 3 levels) and pred2 (continuous) on the response (cont) variable which are collected at 4 different time points (equally spaced interval). Also, consider that I have covariates (age, BMI).
All covariates, pred1, and pred2 are time invarying variables.
Primary hypotheses would be something like-
- Pred2 over 4 time points positively effects response.
- Pred1 levels shows statistically different trajectory for response
- level1 response trajectory is better than the others. (better means- higher response trajectory)
*There are missing values in the repeated responses.
Thank you.
@PaulVelleman is perhaps the best one to answer this question since he wrote a book on EDA and was John Tukey's student at Princeton. He can be contacted on ResearchGate. Best, David Booth
There is one of a good work related to your query : Article Visualization of Categorical Longitudinal and Times Series Data
Also you can contact the University of Sydney research group who working on longitudinal and panel data : https://sydney.edu.au/data-science/
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