2 packages on CRAN
Functions to implements random forest method for model based recursive partitioning. The mob() function, developed by Zeileis et al. (2008), within 'party' package, is modified to construct model-based decision trees based on random forests methodology. The main input function mobforest.analysis() takes all input parameters to construct trees, compute out-of-bag errors, predictions, and overall accuracy of forest. The algorithm performs parallel computation using cluster functions within 'parallel' package.
Functions to perform propensity score matching on rolling entry interventions for which a suitable "entry" date is not observed for nonparticipants. For more details, please reference Witman et al. (2018) <https://onlinelibrary.wiley.com/doi/abs/10.1111/1475-6773.13086>.