Roger J Marshall1. 1. Section of Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, New Zealand. rj.marshall@auckland.ac.nz
Abstract
OBJECTIVE: To illustrate scaled rectangle diagrams as a method for displaying clinical and epidemiological attributes (such as symptoms, signs, results of marker tests, disease, or risk factors). These are quantitative Venn diagrams, but using rectangles instead of circles. STUDY DESIGN AND SETTING: The method is illustrated through examples from various data sets with different types of clinical information. RESULTS: Examples drawing on studies of lung disease, rheumatic fever, blood pressure, lipid levels, sudden infant death syndrome, and low birth weight illustrate the different types of relationships between variables that the scaled rectangle approach can reveal (e.g., high- and low-risk groups; dependent, independent, or co-occurring attributes; effects from choice of cutoff; cumulative distributions; and case-control attributes). CONCLUSION: Scaled rectangle diagrams are a novel way to display clinical data. They show clearly the relative frequency of clinical attributes and the extent to which they are shared characteristics. Features are revealed that might otherwise not have been appreciated.
OBJECTIVE: To illustrate scaled rectangle diagrams as a method for displaying clinical and epidemiological attributes (such as symptoms, signs, results of marker tests, disease, or risk factors). These are quantitative Venn diagrams, but using rectangles instead of circles. STUDY DESIGN AND SETTING: The method is illustrated through examples from various data sets with different types of clinical information. RESULTS: Examples drawing on studies of lung disease, rheumatic fever, blood pressure, lipid levels, sudden infant death syndrome, and low birth weight illustrate the different types of relationships between variables that the scaled rectangle approach can reveal (e.g., high- and low-risk groups; dependent, independent, or co-occurring attributes; effects from choice of cutoff; cumulative distributions; and case-control attributes). CONCLUSION: Scaled rectangle diagrams are a novel way to display clinical data. They show clearly the relative frequency of clinical attributes and the extent to which they are shared characteristics. Features are revealed that might otherwise not have been appreciated.
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