plot.bh | R Documentation |
This function is to graphically summarize Bayesian hierarchical model fits by plotting the coefficients (or odds ratios) and the standard deviation (2*sd). It also can show the p-values.
plot.bh(object = NULL, coefs, sds = NULL, pvalues = NULL, vars.rm = NULL,
threshold = 0.05, show.all.vars = FALSE, show.pvalues = TRUE, gap = 0,
main = " ", cex.main = 0.9, xlim = NULL, cex.var = 0.8, cex.pts = 1,
pch.pts = 20, type = "p", lwd = 1, lty = 1, line = 0, col.pts = "black",
OR = FALSE, add = FALSE)
object |
an object from |
coefs , sds , pvalues |
vector of coefficints ( |
vars.rm |
a vector of variables to be removed; default is |
threshold |
a p-value or a positive integer value to determine variables to be shown: variables with p-value < |
show.all.vars |
logical. If |
show.pvalues |
logical. If |
gap |
a value for the distance between two flanking significant variables. |
main , cex.main , xlim , type , lwd , lty , line |
These arguments are the same as in |
cex.var |
the fontsize of the varible names, default = |
cex.pts |
the size of points, default = |
col.pts |
color of points and segments, default is black. It can be a vector with two elements, which will use specified colors for different
variables determined by the augument |
pch.pts |
symbol of points, default is solid dot. |
OR |
logical. If |
add |
logical. if |
This function plots the estimates of coefficients, intervals and p-values from a fitted GLMs or Cox model. It uses different colors to distinguish between siginificant and insignificant variables based on a threshold.
Nengjun Yi, nyi@uab.edu
plot
, par
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