问题描述
我有以下数据：
DF<-structure(list(ref = structure(c(15L,15L,16L,19L,2L,12L,11L,23L,6L,21L,5L,13L,8L,22L,26L,27L,20L,17L,9L,7L,24L,25L,18L,1L,3L,14L,4L,10L,14L),.Label = c("Bob 2012","Bob 2016","Arnez 2004","Smithy 2013","Smithy 2014","Smithy 2016","Carole 2011","Craig 2014","Fansa 2008","Johnson 2010","Joel 2017","Joelo 2016","Bob2 2017","Bob2 2020","Hunter 2015","Hush 2016","Lock 2012","Mcdoo 2012","Nick 2018","Park 2015","Joe 2012","Sour 2017","Shoe 2008","Vega 2009","West 2004","West2016","Smith 2016"),class = "factor"),yi = c(1,0.909090909090909,1,0.98780487804878,0.933333333333333,0.882352941176471,0.980519480519481,0.977272727272727,0.98019801980198,0.959183673469388,0.982758620689655,0.96969696969697,0.6875,0.75,0.969811320754717,0.0333333333333333,0.064935064935065,0.0227272727272727,0.0204081632653061,0.142857142857143,0.0384615384615384,0.120689655172414,0.0303030303030303,0.0625,0.0625000000000001,0.148148148148148,0.333333333333333,0.0322580645161291,0.0150943396226415,0.027027027027027,0.0182926829268293,0.0588235294117647,0.0324675324675325,0.0416666666666667,0.0408163265306122,0.192307692307692,0.103448275862069,0.03125,0.037037037037037,0.0526315789473685,0.0264150943396226),ci.lb = c(0.968401784273333,0.745137584391619,0.957452087056599,0.954039295289784,0.963597464688465,0.809439442909756,0.67719312002544,0.951199930155904,0.905001120558666,0.929555376052338,0.880663089089027,0.941246506281999,0.880901216198665,0.934891169467222,0.927453022366531,0.874486623056924,0.435962472420225,0.946947080517241,0.937267052265125,0.861434988827223,0.945257646596841,0.384687131024181,0.945252480837292,0.0306637200529119,0.00329369106613314,0.0474215778277017,0.00112833931883988,0.0347070885129207,0.0895601878163022,0.00321663954072449,0.00226571557474109,0.00919930409127839,0.000687698884629828,0.0597984369364536,0.0359775093204114,0.00995385402759386),ci.ub = c(1,0.998207039140277,0.999812850010077,0.998780552481617,0.997483360196549,0.997584224395838,0.999688395336243,0.99931230111537,0.895437964404381,0.992197756884658,0.987557818958737,0.0425479129434015,0.137561603224075,0.11002605111172,0.0949988794413338,0.070444623947662,0.0855442043005818,0.384071178226987,0.157747957353967,0.21886405934029,0.125513376943076,0.249041832299857,0.0530529194827593,0.179245839830917,0.311107006224451,0.628630049521593,0.133296666133586,0.062732947734875,0.0340807242282984,0.112387275591248,0.0458586358986253,0.235428911558493,0.0674429497369029,0.170235847270992,0.119098783801335,0.36946549674197,0.197004260641943,0.129288064181111,0.152166113984736,0.212219059832308,0.0497506289906541),TypeTwo = structure(c(2L,1L),.Label = c("BAR","FOO"),Variable = c("Death","Death","Vein Problems","Gas","Gas")),row.names = c(NA,-61L),yi.names = "yi",ci.lb.names = "ci.lb",ci.ub.names = "ci.ub",digits = c(est = 4,se = 4,test = 4,pval = 4,ci = 4,var = 4,sevar = 4,fit = 4,het = 4),class = c("escalc","data.frame"))
DF%>%ggplot(aes(x=yi,y=ref,xmin=ci.lb,xmax=ci.ub,color=TypeTwo,group=TypeTwo))+geom_point()+geom_errorbarh(height=.1,size=.5)+geom_vline(xintercept = 0,color="black",linetype="dashed",alpha=.5)+facet_grid(Variable~.,scales="free",space="free")+labs(title="Forest Plot Combined",x="Effect Size",y="Study")
看起来像这样：
我想对图表进行重新排序，以使“ Foo”和“ Bar”彼此靠近（如下图所示），并且我在不同的数据集中有单独的“汇总”数据，我想为每个组在每个构面下添加一条线（如果有意义）。如何为此添加新行，但将其保留在构面中？
我完全不知道该怎么做，请帮忙！
解决方法
有很多方法可以解决此问题，但这是其中一种。请注意，由于您在多个方面都有相同的研究，并且TypeTwo不一致，因此我们必须做一些技巧才能在每个方面进行排序。
我也按效果大小排序，因为这很令人愉快并且很常见。
您在Hunter 2015的数据中有一个错误，该错误针对死亡具有两种效果大小，因此这就是为什么其中有一个红色条和一个绿色条的原因。
使用一些随机数据产生平均效果：
library(tidyverse)
avg <- data.frame(
Variable = c('Death','Gas','Vein Problems'),yi = c(0.9,0.1,0.1),ci.lb = c(0.5,0),ci.ub = c(1,0.5,0.5),TypeTwo = 'mean effect',ref = ''
)
DF2 <- bind_rows(DF,avg) %>%
arrange(desc(TypeTwo),yi) %>%
mutate(ref2 = fct_inorder(paste(ref,Variable)))
ggplot(DF2,aes(x=yi,y=ref2,xmin=ci.lb,xmax=ci.ub,color=TypeTwo,group=TypeTwo))+
geom_point()+
geom_errorbarh(height=.1,size=.5)+
geom_vline(xintercept = 0,color="black",linetype="dashed",alpha=.5)+
facet_grid(Variable~.,scales="free",space="free")+
scale_y_discrete(breaks = DF2$ref2,labels = DF2$ref) +
labs(title="Forest Plot Combined",x="Effect Size",y="Study")
