Department of Biostatistics, Columbia Mailman School of Public Health, New York, United States
Tomoko Kitago
Burke Neurological Institute, White Plains, United States; Weill Cornell Medicine, New York, United States
Angel Garcia de la Garza
Department of Biostatistics, Columbia Mailman School of Public Health, New York, United States
Robinson Kundert
Cereneo, Center for Neurology and Rehabilitation, Vitznau, Switzerland
Andreas Luft
Cereneo, Center for Neurology and Rehabilitation, Vitznau, Switzerland; Vascular Neurology and Neurorehabilitation, Department of Neurology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
Cathy Stinear
Department of Medicine, University of Auckland, Auckland, New Zealand
Winston D Byblow
Department of Exercise Sciences, University of Auckland, Auckland, New Zealand
Gert Kwakkel
Rehabilitation Research Centre, Reade, Amsterdam, Netherlands; Rehabilitation Medicine, Amsterdam UMC - Location VUMC, Amsterdam Movement Sciences, Amsterdam, Netherlands
Department of Neurology, Johns Hopkins University, Baltimore, United States; Department of Neuroscience, Johns Hopkins University, Baltimore, United States; Department of Physical Medicine and Rehabilitation, Baltimore, United States; Santa Fe Institute, Santa Fe NM, United States
The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explicitly relates change scores to baseline values – an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or to regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery.
