R 带有ggplot2的自定义林打印。Can';如果没有多个组,CI将超过下限
我编写了一个函数,从回归结果中绘制CI的森林图 我将data.frame与预测器标签($label)、估计($coef)、低ci和高ci($ci.low、$ci.high)、样式($style)一起馈送到函数: 我想在估计值周围显示CI,如果可能的话,对预测值进行分组。对于第一个目标,我翻转轴并使用误差条;对于后者,我在数据框中创建了有标签但没有值的行。结果是: 第一个问题: 正如您所看到的,分组标签是粗体的,没有任何关联的数据。 样式(普通或粗体)在样式列中定义(我计划将其自动化)。问题是,只有当所有标签都不同时,这才有效(注意,我在第一个图中的每个标签上都添加了“2”,以使它们不同);带有重复标签的行仅显示为空白: 我从“精神创伤”标签上取下2号,它就消失了。(而且样式也很混乱) 我想找到一个分组的解决方案,甚至与我的实现完全不同,但没有相同名称的问题 第二个问题: 正如您在两幅图像中看到的,较低的CI条穿过零,这是优势比(并且给定我使用的数据帧中的数字),这是不可能的 这是我的密码:R 带有ggplot2的自定义林打印。Can';如果没有多个组,CI将超过下限,r,plot,ggplot2,R,Plot,Ggplot2,我编写了一个函数,从回归结果中绘制CI的森林图 我将data.frame与预测器标签($label)、估计($coef)、低ci和高ci($ci.low、$ci.high)、样式($style)一起馈送到函数: 我想在估计值周围显示CI,如果可能的话,对预测值进行分组。对于第一个目标,我翻转轴并使用误差条;对于后者,我在数据框中创建了有标签但没有值的行。结果是: 第一个问题: 正如您所看到的,分组标签是粗体的,没有任何关联的数据。 样式(普通或粗体)在样式列中定义(我计划将其自动化)。问题是,
forest.plot <- function(d, xlab = "Coefficients", ylab = "", exp = T, bars = T, lims = NULL){
require(ggplot2)
boundary <- 0
text.pos <- -1.5
if(is.null(lims)) lims <- c(min(d$ci.low, na.rm = T), max(d$ci.high, na.rm = T))
p <- ggplot(d, aes(x=label, y=coef), environment = environment()) +
coord_flip()
if (exp == T){
p <- p + scale_y_log10(labels = round)
boundary <- 1
if(xlab == 'Coefficients') xlab <- 'Odds Ratios'
}
p <- p + geom_hline(yintercept = boundary, lty=2, col = 'darkgray', lwd = 1)
if (bars == T) {
text.pos <- -2
p <- p +
geom_bar(aes(fill = coef > boundary), stat = "identity", width = .3) +
geom_errorbar(aes(ymin = ci.low, ymax = ci.high, lwd = .5), colour = "dodgerblue4", width = 0.05)
}
else p <- p + geom_errorbar(aes(colour = coef > boundary, ymin = ci.low, ymax = ci.high, width = .05, lwd = .5))
if (!is.null(d$style)) style <- d[['style']] else style <- rep('plain', nrow(d))
p <- p + geom_point(colour = 'dodgerblue4', aes(size = 2)) +
scale_x_discrete(limits=rev(d$label)) +
geom_text(aes(label = coef, vjust = text.pos)) +
theme_bw() +
theme(axis.text.x = element_text(color = 'gray30', size = 16),
axis.text.y = element_text(face = rev(style), color = 'gray30', size = 14, hjust=0, angle=0),
axis.title.x = element_text(size = 20, color = 'gray30', vjust = 0),
axis.ticks = element_blank(),
legend.position="none",
panel.border = element_blank()) +
geom_vline(xintercept = 0, lwd = 2) +
ylab(xlab) +
xlab(ylab)
return(p)
}
forest.plot您可以通过创建两个ggplot
对象并通过gridExtra::grid.draw将它们放在一起来获得所需的结果
设立
没有人有任何想法?至少对两个问题中的一个非常有用!
forest.plot <- function(d, xlab = "Coefficients", ylab = "", exp = T, bars = T, lims = NULL){
require(ggplot2)
boundary <- 0
text.pos <- -1.5
if(is.null(lims)) lims <- c(min(d$ci.low, na.rm = T), max(d$ci.high, na.rm = T))
p <- ggplot(d, aes(x=label, y=coef), environment = environment()) +
coord_flip()
if (exp == T){
p <- p + scale_y_log10(labels = round)
boundary <- 1
if(xlab == 'Coefficients') xlab <- 'Odds Ratios'
}
p <- p + geom_hline(yintercept = boundary, lty=2, col = 'darkgray', lwd = 1)
if (bars == T) {
text.pos <- -2
p <- p +
geom_bar(aes(fill = coef > boundary), stat = "identity", width = .3) +
geom_errorbar(aes(ymin = ci.low, ymax = ci.high, lwd = .5), colour = "dodgerblue4", width = 0.05)
}
else p <- p + geom_errorbar(aes(colour = coef > boundary, ymin = ci.low, ymax = ci.high, width = .05, lwd = .5))
if (!is.null(d$style)) style <- d[['style']] else style <- rep('plain', nrow(d))
p <- p + geom_point(colour = 'dodgerblue4', aes(size = 2)) +
scale_x_discrete(limits=rev(d$label)) +
geom_text(aes(label = coef, vjust = text.pos)) +
theme_bw() +
theme(axis.text.x = element_text(color = 'gray30', size = 16),
axis.text.y = element_text(face = rev(style), color = 'gray30', size = 14, hjust=0, angle=0),
axis.title.x = element_text(size = 20, color = 'gray30', vjust = 0),
axis.ticks = element_blank(),
legend.position="none",
panel.border = element_blank()) +
geom_vline(xintercept = 0, lwd = 2) +
ylab(xlab) +
xlab(ylab)
return(p)
}
library(ggplot2)
library(gridExtra)
library(grid)
regression_results <-
structure(list(label = structure(c(9L, 4L, 8L, 2L, 6L, 10L, 3L, 7L, 1L, 5L),
.Label = c(" - frattura esposta", " - frattura esposta 2", " - lembo di perone vs lembo corticoperiostale", " - lembo di perone vs lembo corticoperiostale 2", " - sesso maschile vs femminile", " - sesso maschile vs femminile 2", " - trauma bassa energia", " - trauma bassa energia 2", "Tempo di guarigione 2:", "Tempo di guarigione:"),
class = "factor"),
coef = c(NA, 0.812, 0.695, 1.4, 0.682, NA, 0.812, 0.695, 1.4, 0.682),
ci.low = c(NA, 0.405, 0.31, 1.26, 0.0855, NA, 0.405, 0.31, 1.26, 0.0855),
ci.high = c(NA, 1.82, 0.912, 2.94, 1.01, NA, 1.82, 0.912, 2.94, 1.01),
style = structure(c(1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L),
.Label = c("bold", "plain"), class = "factor")),
.Names = c("label", "coef", "ci.low", "ci.high", "style"),
class = "data.frame",
row.names = c(NA, -10L))
# Set a y-axis value for each label
regression_results$yval <- seq(nrow(regression_results), 1, by = -1)
# Forest plot
forest_plot <-
ggplot(regression_results) +
theme_bw() +
aes(x = coef, xmin = ci.low, xmax = ci.high, y = yval) +
geom_point() +
geom_errorbarh(height = 0.2, color = 'red') +
geom_vline(xintercept = 1) +
theme(
axis.text.y = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.border = element_blank()
) +
ylim(0, 10) +
xlab("Odds Ratio")
# labels, could be extended to show more information
table_plot <-
ggplot(regression_results) +
theme_bw() +
aes(y = yval) +
geom_text(aes(label = gsub("\\s2", "", label), x = 0), hjust = 0) +
theme(
axis.text = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
panel.grid = element_blank(),
panel.border = element_blank()
) +
xlim(0, 6) +
ylim(0, 10)
# build the plot
png(filename = "so-example.png", width = 8, height = 6, units = "in", res = 300)
grid.draw(gridExtra:::cbind_gtable(ggplotGrob(table_plot), ggplotGrob(forest_plot), size = "last"))
dev.off()