This data set is consists of a panel of 50 individuals with 12 observations per individual. The data is based on a regression tree with an initial split based on a dummy variable (
D) and a second split based on time in the branch where
D=1. The observations include both randomly generated individual-specific effects and observation-specific errors.
The data has 600 rows and 5 columns. The columns are:
Ythe target variable
ta numeric predictor ("time")
Da catergorical predictor with two levels, 0 and 1
IDthe identifier for each individual
Xanother covariate (which is intentionally unrelated to the target variable)
Sela, Rebecca J., and Simonoff, Jeffrey S., “RE-EM Trees: A Data Mining Approach for Longitudinal and Clustered Data”, Machine Learning (2011).