Abstract
Current health policy calls for greater use of evidence-based care delivery services to improve patient quality and safety outcomes. Care delivery is complex, with interacting and interdependent components that challenge traditional statistical analytic techniques, in particular, when modeling a time series of outcomes data that might be
Original language | English (US) |
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Pages (from-to) | 4660-4676 |
Number of pages | 17 |
Journal | Statistics in Medicine |
Volume | 36 |
Issue number | 29 |
DOIs | |
State | Published - Aug 29 2017 |
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Dive into the research topics of 'A robust interrupted time series model for analyzing complex health care intervention data'. Together they form a unique fingerprint.Datasets
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Dataset for: A robust interrupted time series model for analyzing complex healthcare intervention data
Cruz, M. (Creator), Bender, M. (Creator), Ombao, H. (Creator), Cruz, M. (Creator) & Bender, M. (Creator), figshare, 2017
DOI: 10.6084/m9.figshare.c.3839242, http://hdl.handle.net/10754/663887
Dataset
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Dataset for: A robust interrupted time series model for analyzing complex healthcare intervention data
Cruz, M. (Creator), Bender, M. (Creator), Ombao, H. (Creator), Cruz, M. (Creator) & Bender, M. (Creator), figshare, Jul 31 2017
DOI: 10.6084/m9.figshare.5259847, http://hdl.handle.net/10754/662377
Dataset