176 Analysis of hierarchical data; Comparing meta-analytical to multilevel estimates
نویسندگان
چکیده
منابع مشابه
Hierarchical Linear Modeling of Multilevel Data
Most data involving organizations are hierarchical in nature and often contain variables measured at multiple levels of analysis. Hierarchical linear modeling (HLM) is a relatively new and innovative statistical method that organizational scientists have used to alleviate some common problems associated with multilevel data, thus advancing our understanding of organizations. This article presen...
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Meta-analysis can be considered a multilevel statistical problem, since information within studies is combined in the presence of potential heterogeneity between studies. Here a general multilevel model framework is developed for meta-analysis to combine either summary data or individual patient outcome data from each study, and to include either study or individual level covariates that might ...
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OBJECTIVE To compare meta-analyses of diagnostic test accuracy using the Moses-Littenberg summary receiver operating characteristic (SROC) approach with those of the hierarchical SROC (HSROC) model. STUDY DESIGN AND SETTING Twenty-six data sets from existing test accuracy systematic reviews were reanalyzed with the Moses-Littenberg model, using equal weighting ("E-ML") and weighting by the in...
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Background and Objectives: Patient safety (PS) is one of the most important and essential elements of quality in healthcare setting. A systematic review and meta-analysis was performed to assess the status of patient safety culture using the Hospital Survey on Patient Safety Culture (HSOPSC). Methods: In this systematic review and meta-analysis study, data were collected through searching dat...
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We present an external-memory algorithm for computing a minimum-cost edit script between two rooted, ordered, labeled trees. The I/O, RAM, and CPU costs of our algorithm are, respectively, 4mn+7m+5n, 6S, andO(MN+(M+N )S1:5), where M and N are the input tree sizes, S is the block size, m = M=S, and n = N=S. This algorithm can make effective use of surplus RAM capacity to quadratically reduce I/O...
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ژورنال
عنوان ژورنال: Occupational and Environmental Medicine
سال: 2013
ISSN: 1351-0711,1470-7926
DOI: 10.1136/oemed-2013-101717.176