我运行了许多模型，每个模型有两个估计参数，有五个组和两种治疗方法。我试图在一个大面板图中绘制这些估计值的置信区间。因为，我已经模拟了这些数据集，所以我希望能够包含一条虚线，表示我在练习开始时设置的参数的“真实值”以供引用，这样我们就可以看到模型估计值包括真实值。我可以很好地做到这一点，但我想在图例中添加另一行，显示“黑色虚线”=真实值。
这是代码示例。第一组代码有效，并且不包括图例中的黑色虚线。
group = c("group1", "group2", "group3", "group4", "group5")
treatment = c("treatment1", "treatment2")
estimates = c("estim1", "estim2")
parameters = c("param1", "param2")
means = c(0, 0, 5, 0, -5, 0, 0, 7, -5, 10, -5, 0, 0, 0, 0, 0, -5, 0, 0, 10)
UL = c(.5, .5, 5.5, .5, -4.5, 0.5, 0.5, 7.5, -4.5, 10.5, -4.5, .5, .5, .5, .5, .5, -4.5, .5, .5, 10.5)
LL = c(-.5, -.5, 4.5, -.5, -5.5, -.5, -.5, 6.5, -4.5, 9.5, -4.5, -.5, -.5, -.5, -.5, -.5, -4.5, -.5, -.5, 9.5)
values = c(.2, -.2, 5.2, -.3, -4.7, -.1, -.2, 6.9, -5.3, 10.1, -4.4, 0.1, 0.2, 0.3, 0.1, -0.1, -4.9, -.2, -.2, 9.9)
df = data.frame(
group = rep(rep(group, each = 2), 2),
treatment = rep(treatment, each = 10),
estimates = rep(estimates, 10),
LL = LL,
means = means,
UL = UL,
parameters = rep(parameters, 10),
values = values
)
ggplot(data = df, aes(x = as.factor(estimates), y = means, color = estimates))+
geom_point()+
geom_errorbar(aes(ymin = LL, ymax = UL), width=.1, position = position_dodge(0.1))+
geom_segment(x = rep(c(.6, 1.6), 10), xend = rep(c(1.4, 2.4), 10),
y = values, yend = values, col = "black",
linetype = 3)+
scale_x_discrete(labels = c(expression(beta[1]), expression(beta[2])))+
xlab("Beta coefficient type")+ylab("Confidence Interval of Estimate")+
ggtitle("Coefficient Estimates")+
facet_grid(row = vars(treatment), col = vars(group))+
scale_color_manual(name = "Symbols",
values = c("estim1" = "#F8766D", "estim2" = "#00BFC4"),
labels = c(expression(beta[1]),
expression(beta[2])))
scale_shape_manual(values = c("b1" = 16,
"b2" = 16)+
scale_linetype_manual(values = c("b1" = 1,
"b2" = 1))
第二组代码不起作用，但这是我最好的尝试，我应该做什么来尝试获得图例中的黑色虚线。
ggplot(data = df, aes(x = as.factor(estimates), y = means, color = estimates))+
geom_point()+
geom_errorbar(aes(ymin = LL, ymax = UL), width=.1, position = position_dodge(0.1))+
geom_segment(x = rep(c(.6, 1.6), 10), xend = rep(c(1.4, 2.4), 10),
y = values, yend = values, col = "black",
linetype = 3)+
scale_x_discrete(labels = c(expression(beta[1]), expression(beta[2])))+
xlab("Beta coefficient type")+ylab("Confidence Interval of Estimate")+
ggtitle("Coefficient Estimates")+
facet_grid(row = vars(treatment), col = vars(group))+
scale_color_manual(name = "Symbols",
values = c("estim1" = "#F8766D", "estim2" = "#00BFC4"),
#"" = "#00000"),
labels = c(expression(beta[1]),
expression(beta[2])))#,
#"True Value"))#+
scale_shape_manual(values = c("b1" = 16,
"b2" = 16,
"" = 0))+
scale_linetype_manual(values = c("b1" = 1,
"b2" = 1,
"b3" = 3))
我还认为也许我可以尝试重新调整 df$estimates 列的级别，以包含三个级别(现有)“estim1”、“estim2”和一个没有观察结果的虚拟“真实值”级别，但我'我担心这只会在 x 轴子标签上的 12 个图上添加一个空的“真实值”刻度。
感谢您的帮助。
最佳答案
将 geom_segment 的线型映射到 aes 内名为“True value”的字符串，然后添加 scale_linetype_manual 调用。这将创建一个单独的图例条目，该条目与您的段的外观相匹配并具有正确的标签。
ggplot(data = df, aes(x = as.factor(estimates), y = means, color = estimates)) +
geom_point() +
geom_errorbar(aes(ymin = LL, ymax = UL), width=.1,
position = position_dodge(0.1)) +
geom_segment(x = rep(c(.6, 1.6), 10), xend = rep(c(1.4, 2.4), 10),
y = values, yend = values, col = "black",
aes(linetype = "True value")) +
scale_x_discrete(labels = c(expression(beta[1]), expression(beta[2]))) +
xlab("Beta coefficient type")+ylab("Confidence Interval of Estimate") +
ggtitle("Coefficient Estimates") +
facet_grid(row = vars(treatment), col = vars(group)) +
scale_color_manual(name = "Symbols",
values = c("estim1" = "#F8766D", "estim2" = "#00BFC4"),
labels = c(expression(beta[1]),
expression(beta[2]))) +
scale_linetype_manual(values = 3, name = NULL)
关于r - 如何向 ggplot 图例添加新的(自定义)变量，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/73179099/