我想就冒险和性别做2个散点图。我有12个研究,每个研究都有男性和女性的数据(均值,效应大小,抽样方差)。每项研究的均值差异很大,在一项研究中,男性为1490,女性为1200,在另一项研究中,男性为33,女性为25。我想在同一张图上进行2个不同的散点图绘制。 X轴应为年龄,Y轴应为冒险。我需要2条不同的曲线,一条用于女性,另一条用于男性。我该如何融合这两条曲线?甚至有可能将所有内容放在一张图上吗?
我已经尝试过使用ggplot2,geom_point()和metafor软件包。
# yi = effect sizes of each study
# vi = sampling variance
# data = mydata
library("metafor")
# adjust margins so the space is better used
par(mar=c(5,5,1,2))
# fit mixed-effects model with age as predictor
res <- rma(yi, vi, mods = ~ magewomen, data=mydata)
# calculate predicted risk ratios for womens’ age 0-30.
preds <- predict(res, newmods=c(0:35), transf=exp)
# calculate point sizes by rescaling the standard errors
wi <- 1/sqrt(mydata$vi)
size <- 0.5 + 3.0 * (wi - min(wi))/(max(wi) - min(wi))
# plot the risk ratios against women’s age
women <- plot(mydata$magewomen, exp(mydata$yi), pch=19, cex=size,
xlab="womens age", ylab="Risk",
las=1, bty="l", log="y")
# add predicted values (and corresponding CI bounds)
lines(0:35, preds$pred)
lines(0:35, preds$ci.lb, lty="dashed")
lines(0:35, preds$ci.ub, lty="dashed")
# Same procedure, just for men
# adjust margins so the space is better used
par(mar=c(5,5,1,2))
# fit mixed-effects model with men’s age as predictor
res2 <- rma(yi, vi, mods = ~ magemen, data=mydata)
# calculate predicted risk ratios for men’s age from 0-30
preds2 <- predict(res2, newmods=c(0:35), transf=exp)
# calculate point sizes by rescaling the standard errors
wi <- 1/sqrt(mydata$vi)
size <- 0.5 + 3.0 * (wi - min(wi))/(max(wi) - min(wi))
# plot the risk ratios against men’s age
men <- plot(mydata$magemen, exp(mydata$yi), pch=19, cex=size,
xlab="mens age", ylab="Risk",
las=1, bty="l", log="y")
# add predicted values (and corresponding CI bounds)
lines(0:35, preds$pred)
lines(0:35, preds$ci.lb, lty="dashed")
lines(0:35, preds$ci.ub, lty="dashed")
我希望能够将2个散点图融合为一个,但我不知道如何。另外,这两个散点图看起来非常相似,我认为不应该如此。
答案 0 :(得分:0)
我认为在辅助轴上绘制第二个图应该可以解决您的问题。在第二个new = T
调用中添加par()
作为参数,第二个图将绘制在第一个图的顶部。
然后在代码末尾运行axis(side=4)
,以在图形的右侧生成第二个绘图的轴