将 metafor::rma 与 geom_smooth 一起使用？

Question

我想使用 metafor::rma() 作为 ggplot 的平滑器。我已经尝试了各种方法来让它继续运行，但似乎都没有奏效。这是一个最小（非）工作示例：

# Libraries
library(metafor)
library(ggplot2)

# Some data preparation
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

# Scatterplot of the data
figure1 <- ggplot(dat, aes(y = yi, x = ablat)) + geom_point()
figure1

# Various attempts that lead to various error messages :(
figure2a <- ggplot(dat, aes(y = yi, x = ablat)) +
           geom_point() + geom_smooth(method = metafor::rma())

figure2b <- ggplot(dat, aes(y = yi, x = ablat)) +
  geom_point() + geom_smooth(method = metafor::rma(y = yi, vi = vi))

figure2c <- ggplot(dat, aes(y = yi, x = ablat)) +
  geom_point() + geom_smooth(method = metafor::rma(y = dat$yi, vi = dat$vi))

figure2d <- ggplot(dat, aes(y = yi, x = ablat)) +
  geom_point() + geom_smooth(method = metafor::rma(yi = yi, vi = vi, data = dat), formula = yi ~ ablat)

figure2e <- ggplot(dat, aes(y = yi, x = ablat)) +
  geom_point() + geom_smooth(method = metafor::rma(), method.args = list(yi = dat$yi, vi = dat$vi, method = "EB"))

我做错了什么？谢谢

Answer 1

我曾短暂尝试过使其与geom_smooth() 一起工作，但我不是ggplot2 的重度用户并且没有成功。但正如@Tjebo 建议的那样，您可以使用predict() 计算预测值，然后使用geom_line() 和geom_ribbon() 添加元素。这是一个例子：

library(metafor)
library(ggplot2)

dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
res <- rma(yi, vi, mods = ~ ablat, data=dat)
pred <- as.data.frame(predict(res, newmods = seq(0,60,by=1), addx=TRUE))
names(pred)[8] <- "ablat"

ggplot(dat, aes(x = ablat)) +
   geom_point(aes(y = yi)) +
   geom_line(data = pred, aes(x = ablat, y = pred)) +
   geom_ribbon(data = pred, aes(ymin = ci.lb, ymax = ci.ub), fill = "blue", alpha = 0.2)