plot.frag.study.all {fragility} | R Documentation |
Plot Method for "frag.study.all" Objects
Description
Visualizes the fragility of an individual study with a binary outcome.
Usage
## S3 method for class 'frag.study.all'
plot(x, method, modify0, modify1, trun,
xlab, ylab, xlim, ylim, cex.pts, cex.legend.pval, cex.legend.title,
col.ori, col.ori.hl, col.f.hl, col.sig, lty.ori, lwd.ori,
pch, pch.ori, pch.ori.hl, pch.f, pch.f.hl, pch.trun,
adjust.legend, adjust.seg, legend.pvals, ...)
Arguments
x |
an object of class |
method |
a character string ( |
modify0 |
a logical value indicating whether event status is modified in group 0 for plotting. The default is |
modify1 |
a logical value indicating whether event status is modified in group 1 for plotting. The default is |
trun |
a positive numeric value indicating truncation of p-value (on a base-10 logarithmic scale); p-values smaller than this threshold (10^ |
xlab |
a label for the x axis. |
ylab |
a label for the y axis. |
xlim |
the x limits |
ylim |
the y limits |
cex.pts |
the size of points in the plot (the default is 0.5). |
cex.legend.pval |
the text size of p-values in the legend (the default is 0.6). It is only used when both arguments |
cex.legend.title |
the size of the legend title (the default is 1). It is only used when both arguments |
col.ori |
the color of the line(s) depicting the original data (without event status modifications). The default is |
col.ori.hl |
the color of the point depicting the original data (without event status modifications). The default is |
col.f.hl |
the color of the point(s) for highlighting the minimal event status modifications for altering statistical significance or non-significance. The default is |
col.sig |
a vector of two colors for non-significant and significant results, accordingly. The default includes |
lty.ori |
the type of the line(s) depicting the original data (without event status modifications). The default is 2 (dashed). |
lwd.ori |
the width of the line(s) depicting the original data (without event status modifications). The default is 1. |
pch |
the symbol of the points in the plot. The default is 16 (filled circle) when both arguments |
pch.ori |
the symbol of the point depicting the original data (without event status modifications). The default is 15 (filled square). |
pch.ori.hl |
the symbol of the point for highlighting the original data (without event status modifications). The default is 0 (square). It is only used when both arguments |
pch.f |
the symbol of the point depicting the original data (without event status modifications). The default is 15 (filled square). |
pch.f.hl |
the symbol of the point(s) for highlighting the minimal event status modifications for altering statistical significance or non-significance. The default is 2 (triangle point up). It is only used when both arguments |
pch.trun |
the symbol of the point(s) depicting truncated p-values. The default is 3 (plus). It is only used when only one of the arguments |
adjust.legend |
a positive numeric value for adjusting the width of the legend of p-values. The default is 1. |
adjust.seg |
a positive integer for adjusting the number of segments in the legend of p-values. The default is 10. |
legend.pvals |
a numeric value or a vector of numeric values that give additional p-values (e.g., 0.005 and 0.1) to be shown in the legend. The default is |
... |
other arguments that can be passed to |
Details
When both arguments modify0
and modify1
are TRUE
, the generated plot presents p-values (with different colors representing their magnitudes) based on all possible event status modifications. The modifications in group 0 are presented on the x axis, and those in group 1 are presented on the y axis. When only one of the arguments modify0
and modify1
is TRUE
, a scatter plot is generated, which presents p-values (on a base-10 logarithmic scale) on the y axis against event status modifications in group 0 (if modify0
= TRUE
) or group 1 (if modify1
= TRUE
) on the x axis.
Value
None.
References
Lin L (2021). "Factors that impact fragility index and their visualizations." Journal of Evaluation in Clinical Practice, 27(2), 356–64. <doi: 10.1111/jep.13428>
Lin L, Chu H (2022). "Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package." PLOS ONE, 17(6), e0268754. <doi: 10.1371/journal.pone.0268754>