Simulated dataset of a randomized clinical trial (N = 150) to illustrate fitting of (G)LMM trees.
A data frame containing 150 observations on 6 variables:
numeric. Continuous treatment outcome variable (range: 3-16, M = 9.12, SD = 2.66).
factor. Binary treatment variable.
factor. Indicator for cluster with 10 levels.
numeric. Continuous partitioning variable (range: 18-69, M = 45, SD = 9.56).
numeric. Continuous partitioning variable (range: 3-18, M = 10.26, SD = 3.05).
numeric. Continuous partitioning variable (range: 1-17, M = 6.97, SD = 2.90).
factor. Binarized treatment outcome variable (0 = recovered, 1 = not recovered.
The data were generated such that the duration and anxiety covariates
characterized three subgroups with differences in treatment effects. The
cluster variable was used to introduce a random intercept that should
be accounted for. The treatment outcome is an index of depressive symptomatology.
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