The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Yong Chen - One of the best experts on this subject based on the ideXlab platform.
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the galaxy plot a new Visualization Tool for bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Haitao Chu, Yong ChenAbstract:Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive Visualization Tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
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galaxy plot a new Visualization Tool of bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Yong ChenAbstract:Funnel plots have been widely used to detect small study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a two-dimensional space. We illustrate the use of galaxy plot by two case studies, including a meta-analysis of hypertension trials with studies from 1979 to 1991, and a meta-analysis of structured telephone support or non-invasive telemonitoring with studies from 1966 to 2015. The galaxy plot is an intuitive Visualization Tool that can aid in interpretation of results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
Chuan Hong - One of the best experts on this subject based on the ideXlab platform.
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the galaxy plot a new Visualization Tool for bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Haitao Chu, Yong ChenAbstract:Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive Visualization Tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
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galaxy plot a new Visualization Tool of bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Yong ChenAbstract:Funnel plots have been widely used to detect small study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a two-dimensional space. We illustrate the use of galaxy plot by two case studies, including a meta-analysis of hypertension trials with studies from 1979 to 1991, and a meta-analysis of structured telephone support or non-invasive telemonitoring with studies from 1966 to 2015. The galaxy plot is an intuitive Visualization Tool that can aid in interpretation of results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
Robert J Brunner - One of the best experts on this subject based on the ideXlab platform.
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vizic a jupyter based interactive Visualization Tool for astronomical catalogs
Astronomy and Computing, 2017Co-Authors: Carrasco M Kind, Robert J BrunnerAbstract:Abstract The ever-growing datasets in observational astronomy have challenged scientists in many aspects, including an efficient and interactive data exploration and Visualization. Many Tools have been developed to confront this challenge. However, they usually focus on displaying the actual images or focus on visualizing patterns within catalogs in a predefined way. In this paper we introduce Vizic , a Python Visualization library that builds the connection between images and catalogs through an interactive map of the sky region. Vizic visualizes catalog data over a custom background canvas using the shape, size and orientation of each object in the catalog. The displayed objects in the map are highly interactive and customizable comparing to those in the observation images. These objects can be filtered by or colored by their property values, such as redshift and magnitude. They also can be sub-selected using a lasso-like Tool for further analysis using standard Python functions and everything is done from inside a Jupyter notebook. Furthermore, Vizic allows custom overlays to be appended dynamically on top of the sky map. We have initially implemented several overlays, namely, Voronoi, Delaunay, Minimum Spanning Tree and HEALPix grid layer, which are helpful for visualizing large-scale structure. All these overlays can be generated, added or removed interactively with just one line of code. The catalog data is stored in a non-relational database, and the interfaces have been developed in JavaScript and Python to work within Jupyter Notebook, which allows to create customizable widgets, user generated scripts to analyze and plot the data selected/displayed in the interactive map. This unique design makes Vizic a very powerful and flexible interactive analysis Tool. Vizic can be adopted in variety of exercises, for example, data inspection, clustering analysis, galaxy alignment studies, outlier identification or just large scale Visualizations.
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vizic a jupyter based interactive Visualization Tool for astronomical catalogs
arXiv: Instrumentation and Methods for Astrophysics, 2017Co-Authors: Carrasco M Kind, Robert J BrunnerAbstract:The ever-growing datasets in observational astronomy have challenged scientists in many aspects, including an efficient and interactive data exploration and Visualization. Many Tools have been developed to confront this challenge. However, they usually focus on displaying the actual images or focus on visualizing patterns within catalogs in a predefined way. In this paper we introduce Vizic, a Python Visualization library that builds the connection between images and catalogs through an interactive map of the sky region. Vizic visualizes catalog data over a custom background canvas using the shape, size and orientation of each object in the catalog. The displayed objects in the map are highly interactive and customizable comparing to those in the images. These objects can be filtered by or colored by their properties, such as redshift and magnitude. They also can be sub-selected using a lasso-like Tool for further analysis using standard Python functions from inside a Jupyter notebook. Furthermore, Vizic allows custom overlays to be appended dynamically on top of the sky map. We have initially implemented several overlays, namely, Voronoi, Delaunay, Minimum Spanning Tree and HEALPix grid layers, which are helpful for visualizing large-scale structure. All these overlays can be generated, added or removed interactively with one line of code. The catalog data is stored in a non-relational database, and the interfaces were developed in JavaScript and Python to work within Jupyter Notebook, which allows to create custom widgets, user generated scripts to analyze and plot the data selected/displayed in the interactive map. This unique design makes Vizic a very powerful and flexible interactive analysis Tool. Vizic can be adopted in variety of exercises, for example, data inspection, clustering analysis, galaxy alignment studies, outlier identification or simply large-scale Visualizations.
Stephen E Kimmel - One of the best experts on this subject based on the ideXlab platform.
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the galaxy plot a new Visualization Tool for bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Haitao Chu, Yong ChenAbstract:Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive Visualization Tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
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galaxy plot a new Visualization Tool of bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Yong ChenAbstract:Funnel plots have been widely used to detect small study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a two-dimensional space. We illustrate the use of galaxy plot by two case studies, including a meta-analysis of hypertension trials with studies from 1979 to 1991, and a meta-analysis of structured telephone support or non-invasive telemonitoring with studies from 1966 to 2015. The galaxy plot is an intuitive Visualization Tool that can aid in interpretation of results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
Lingzhen Zeng - One of the best experts on this subject based on the ideXlab platform.
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the galaxy plot a new Visualization Tool for bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Haitao Chu, Yong ChenAbstract:Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive Visualization Tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
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galaxy plot a new Visualization Tool of bivariate meta analysis studies
American Journal of Epidemiology, 2020Co-Authors: Chuan Hong, Richard D Riley, Rui Duan, Lingzhen Zeng, Rebecca A Hubbard, Thomas Lumley, Stephen E Kimmel, Yong ChenAbstract:Funnel plots have been widely used to detect small study effects in the results of univariate meta-analyses. However, there is no existing Visualization Tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new Visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a two-dimensional space. We illustrate the use of galaxy plot by two case studies, including a meta-analysis of hypertension trials with studies from 1979 to 1991, and a meta-analysis of structured telephone support or non-invasive telemonitoring with studies from 1966 to 2015. The galaxy plot is an intuitive Visualization Tool that can aid in interpretation of results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.
