Study Strap and Multi-Study Learning Algorithms

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Documentation for package ‘studyStrap’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

cmss	Covariate-Matched Study Strap for Multi-Study Learning: Fits accept/reject algorithm based on covariate similarity measure
fatTrim	fatTrim: Supporting function to reduce the size of models
merged	Merged Approach for Multi-Study Learning: fits a single model on all studies merged into a single dataframe.
sim.metrics	Study Strap similarity measures: Supporting function used as the default similarity measures in Study Strap, SSE, and CMSS algorithms. Compares similarity in covaraite profiles of 2 studies.
ss	The Study Strap for Multi-Study Learning: Fits Study Strap algorithm
sse	Trained-on-Observed-Studies Ensemble (Study-Specific Ensemble) for Multi-Study Learning: fits one or more models on each study and ensembles models.
studyStrap.predict	Study Strap Prediction Function: Makes predictions on object of class "ss"