Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
نویسندگان
چکیده
منابع مشابه
Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
OBJECTIVE The classification of complex or rare patterns in clinical and genomic data requires the availability of a large, labeled patient set. While methods that operate on large, centralized data sources have been extensively used, little attention has been paid to understanding whether models such as binary logistic regression (LR) can be developed in a distributed manner, allowing research...
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BACKGROUND In biomedical research, data sharing and information exchange are very important for improving quality of care, accelerating discovery, and promoting the meaningful secondary use of clinical data. A big concern in biomedical data sharing is the protection of patient privacy because inappropriate information leakage can put patient privacy at risk. METHODS In this study, we deployed...
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Standard inference techniques are only valid if the design is ignorable. Two approaches that take the design into account are compared using binary logistic regression. The modelbased approach includes relevant design variables as independents and the designbased approach use design weights. The approaches are exemplified using a cross-sectional stratified mail survey, where associations betwee...
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ژورنال
عنوان ژورنال: Journal of the American Medical Informatics Association
سال: 2012
ISSN: 1067-5027,1527-974X
DOI: 10.1136/amiajnl-2012-000862