请在下方q找到我的数据p
我想合并一个library(metafor)用两个计算的森林图ggplots
我用gridArrangeand尝试了多种方法par()，但没有任何成功。我知道关于这个主题有几个主题，但没有一个涉及ggplot和metafor
合并后的图应该这样排列：
PLOT 1和PLOT 2基于以下数据w
w <- structure(list(WHO = c(1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 2L,
3L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 4L, 4L, 1L, 4L, 1L, 2L, 1L, 4L, 1L, 4L, 4L, 4L,
4L, 3L, 3L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 2L, 1L, 2L, 2L, 4L, 4L,
4L, 2L, 4L, 1L, 4L, 4L, 2L, 4L, 4L, 3L, 4L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L,
3L, 4L, 3L, 4L, 3L), response = c(0L, 1L, 0L, 0L, 0L, 1L, 1L,
1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 1L, NA, 1L), Death = c(0L, 1L, 1L, 0L, 0L,
1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L,
1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, NA, 1L)), class = "data.frame", row.names = c(NA,
-111L))
PLOT 1 基于此脚本。
yaks <- c(0,2,4,6,8,10,12,14,16,18)
j <- ggplot() +
geom_bar(mapping = aes(x = w$WHO[w$response==1]), stat = "count", alpha=0.2, colour="#1C73C2", fill="#ECF0F9") +
scale_x_discrete(name="", drop = FALSE, labels =c("WHO-I\nn=32","WHO-II\nn=23","WHO-III\nn=16", "Unknown\nn=5")) +
theme(axis.text.x = element_text(color = "grey20", size = 11))
j <-
j %+% scale_y_continuous(name = "Progression", breaks=yaks, sec.axis = sec_axis(~ . * 1 , name = "Progression rate per 100 person-yrs", breaks=yaks, labels=c("0","40","80","120","160","200","240","280","320","360"))) +
coord_cartesian(ylim=c(0, 18)) +
theme(axis.text.y.right = element_text(color = "red", size = 11), axis.title.y=element_text(size=14,face="bold", margin = margin(t = 0, r = 20, b = 0, l = 0))) +
theme(axis.text.y = element_text(color = "#1C73C2", size = 11), axis.title.y.right=element_text(size=14,face="bold", margin = margin(t = 0, r = 0, b = 0, l = 20)))
j +
geom_point(mapping = aes(x = 1, y = 0.2677376), size=10, alpha=0.7, shape=18, colour="red") +
geom_point(mapping = aes(x = 2, y = 3.2870709), size=10, shape=18,alpha=0.7, colour="red") +
geom_point(mapping = aes(x = 3, y = 16.98), size=10, shape=18,alpha=0.7, colour="red") +
annotate("text", x = c(1,2,3, 4) , y = c(-0.5, 2.2870709, 15.98, 0.5), label = c("5.4","65.7","339.6", "0 events"), col="red", fontface=2, cex=4)
看起来像这样：
而PLOT 2基于此脚本
j <- ggplot() +
geom_bar(mapping = aes(x = w$WHO[w$Death==1]), stat = "count", alpha=0.2, colour="#1C73C2", fill="#ECF0F9")
yaks <- c(0,2,4,6,8,10,12,14,16,18)
j <-
j %+% scale_y_continuous(name = "Deaths", breaks=yaks, sec.axis = sec_axis(~ . * 1 , name = "Mortality rate per 100 person-yrs", breaks=yaks, labels=c("0","5","10","15","20","25","30","35","40","45"))) +
coord_cartesian(ylim=c(0, 18)) +
theme(axis.text.y.right = element_text(color = "red", size = 11), axis.title.y=element_text(size=14,face="bold",margin = margin(t = 0, r = 20, b = 0, l = 0))) +
theme(axis.text.y = element_text(color = "#1C73C2", size = 11), axis.title.y.right=element_text(size=14,face="bold",margin = margin(t = 0, r = 0, b = 0, l = 20)))
j <-
j +
geom_point(mapping = aes(x = 1, y = 3.329993), size=10,alpha=0.7, shape=18, colour="red") +
geom_point(mapping = aes(x = 2, y = 12.424504), size=10,alpha=0.7, shape=18, colour="red") +
geom_point(mapping = aes(x = 3, y = 17.23519), size=10, alpha=0.7,shape=18, colour="red") +
geom_point(mapping = aes(x = 4, y = 4.549763), size=10, alpha=0.7, shape=18, colour="red") +
annotate("text", x = c(1,2,3,4) , y = c(2.329993, 11.424504, 16.23519,3.549763 ), label = c("8.3","31.1","43.1","11.4"), col="red", fontface=2, cex=4)
j + scale_x_continuous(name="", breaks = c(1,2,3,4), labels =c("WHO-I\nn=37","WHO-II\nn=29","WHO-III\nn=19","Unknown\nn=25")) +
theme(axis.text.x = element_text(color = "grey20", size = 11))
看起来像这样：
最后，PLOT 3是来自metafor
森林图如下所示：
有以下数据
q <- structure(list(study = structure(c(2L, 4L, 7L, 3L, 5L, 1L, 8L,
6L, 9L), .Label = c("WHO-I versus Unknown ", "WHO-I versus WHO-II",
"WHO-I versus WHO-II ", "WHO-I versus WHO-III", "WHO-I versus WHO-III ",
"WHO-II versus Unknown", "WHO-II versus WHO-III", "WHO-II versus WHO-III ",
"WHO-III versus Unknown"), class = "factor"), order = 9:1, x1i = c(4L,
4L, 15L, 9L, 9L, 9L, 15L, 15L, 12L), n1i = c(32L, 32L, 23L, 37L,
37L, 37L, 29L, 29L, 19L), t1i = c(74.7, 74.7, 22.8, 108.1, 108.1,
108.1, 48.3, 48.3, 27.9), x2i = c(15L, 15L, 15L, 15L, 12L, 9L,
12L, 9L, 9L), n2i = c(23L, 16L, 16L, 29L, 19L, 25L, 19L, 25L,
25L), t2i = c(22.8, 4.4, 4.4, 48.3, 27.9, 79.1, 27.9, 79.1, 79.1
), ir1 = c(5.4, 5.4, 65.7, 8.3, 8.3, 8.3, 31.1, 31.1, 43.1),
ir2 = c(65.7, 339.6, 339.6, 31.1, 43.1, 11.4, 43.1, 11.4,
11.4)), class = "data.frame", row.names = c(NA, -9L))
和脚本
q <- escalc(measure="IRR", x1i=x1i, t1i=t1i, x2i=x2i, t2i=t2i, data=q)
q1 <- rma(yi, vi, data=q, slab=paste(study, sep=", "), method = "REML")
## Forest
forest(q1, xlim=c(-27,8), atransf=exp, showweights = FALSE, psize = 1.2, refline=log(1),
cex=0.95, ylim=c(0.1, 17), font=1, col="white", border="white", order=order(q$order),
ilab=cbind(q$x1i, q$t1i, q$ir1, q$x2i, q$t2i,q$ir2),
ilab.xpos=c(-19.3,-17,-15,-12.3,-10,-8),
rows=c(2:7,11:13),xlab="Rate ratios", mlab="")
# Headlines
text(c(-19,-16.8,-15,-12,-9.8,-8) ,15.7,font=1, cex=0.9, c("Events\n per total", "Person-\nyrs", "IR", "Events\n per total", "Person-\nyrs","IR"))
text(c(-18.75,-18.75,-18.65) ,c(13,12,11),font=1, cex=0.94, c("/ 32", "/ 32", " / 23"))
text(c(-18.75,-18.75,-18.75) ,c(7,6,5),font=1, cex=0.94, c("/ 37", "/ 37", "/ 37"))
text(c(-18.65,-18.65,-18.65) ,c(4,3,2),font=1, cex=0.94, c(" / 29", " / 29", " / 19"))
text(c(-11.65,-11.65,-11.65) ,c(13,12,11),font=1, cex=0.94, c(" /23", " /16", " /16"))
text(c(-11.65,-11.65,-11.75) ,c(7,6,5),font=1, cex=0.94, c(" /29", "/19", " /25"))
text(c(-11.65,-11.75,-11.75) ,c(4,3,2),font=1, cex=0.94, c("/19", " / 25", " / 25"))
text(8 ,15.7,font=1, "Rate ratio [95% CI]", pos=2, cex=1)
text(-27 ,c(14,8),font=2, c("Progression rates","Mortality rates"), pos=4, cex=0.9)
text(-27 ,c(1,10),font=1, c("Cohort: 110 patients included","Cohort: 76 patients included"), pos=4, cex=0.8)