A new visualization method that simultaneously presents the effect sizes of bivariate outcomes and their standard errors in a two-dimensional space.
galaxy(data, y1, s1, y2, s2, scale1, scale2, scale.adj,
corr, group, study.label, annotate, xlab, ylab, main, legend.pos)
dataset with at least 4 columns for the effect sizes of the two outcomes and their standard errors
column name for outcome 1, default is 'y1'
column name for standard error of y1
, default is 's1'
column name for outcome 2, default is 'y2'
column name for standard error of y2
, default is 's2'
parameter for the length of the cross hair: the ellipse width is scale1 / s1 * scale.adj
parameter for the length of the cross hair: the ellipse height is scale2 / s2 * scale.adj
a pre-specified parameter to adjust for scale1
and scale2
column name for within-study correlation
column name for study group
column name for study label
logical specifying whether study label should be added to the plot, default is FALSE.
x axis label, default y1
y axis label, default y2
main title
The position of the legend for study groups if group
is specified, see legend
, default is 'bottomright'.
Chuan Hong, Chongliang Luo, Yong Chen
This function returns the galaxy plot to visualize bivariate meta-analysis data, which faithfully retains the information in two separate funnel plots, while providing useful insights into outcome correlations, between-study heterogeneity and joint asymmetry. Galaxy plot: a new visualization tool of bivariate meta-analysis studies. 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. 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.
Hong, C., Duan, R., Zeng, L., Hubbard, R., Lumley, T., Riley, R., Chu, H., Kimmel, S., and Chen, Y. (2020) Galaxy Plot: A New Visualization Tool of Bivariate Meta-Analysis Studies, American Journal of Epidemiology, https://doi.org/10.1093/aje/kwz286.
data(sim_dat)
galaxy(data=sim_dat, scale.adj = 0.9, corr = 'corr', group = 'subgroup',
study.label = 'study.id', annotate = TRUE, main = 'galaxy plot')
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