Question

我发现有一种方法可以使用＆＃39; metafor＆＃39;来创建摘要估算的森林图。包，可在此处找到：Meta-analysis: Forest plot of summary estimates using metafor package

是否还有meta包的解决方案？通过30多项研究，byvar函数生成了一个不适合窗口的森林图。

Answer 1

这是一个例子：

### the data

d <- structure(list(study = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
7L, 8L, 8L, 8L, 10L, 9L, 11L, 11L, 12L, 13L, 14L, 14L, 15L, 16L, 
17L, 18L), .Label = c("Bort et al. 2012                ", "Boyl et al. 2004                ", 
"Cart et al. 2007                ", "Coryet al. 2009                 ", 
"Cosoff 1998                     ", "Dell'a 2011                     ", 
"Dilan 2003                      ", "Dilton et al. 1997              ", 
"Mac et al. 2001                 ", "Man et al. 2006                 ", 
"Okan 2011                       ", "Orol et al. 2006                ", 
"Pinto et al. 2003               ", "Simone et al. 2004              ", 
"Strahowski et al. 1992          ", "Tamara 2002                     ", 
"Viera et al. 2001               ", "Zucchi et al. 2006              "
), class = "factor"), xi = c(60, 40, 13, 107, 3, 32, 1, 16, 33, 
1, 20, 46, 27, 30, 22, 78, 35, 33, 5, 2, 4, 3, 4), ni = c(200, 
140, 56, 427, 20, 508, 25, 19, 53, 32, 44, 191, 288, 50, 46, 
918, 151, 360, 115, 41, 70, 129, 80), group = structure(c(3L, 
3L, 1L, 3L, 3L, 3L, 1L, 1L, 2L, 1L, 1L, 3L, 3L, 1L, 2L, 3L, 3L, 
1L, 2L, 1L, 1L, 4L, 4L), .Label = c("anxiety     ", "depression  ", 
"mixed       ", "remission   "), class = "factor")), .Names = c("study", 
"xi", "ni", "group"), row.names = c(NA, -23L), class = "data.frame", codepage = 1252L)

attach(d)

### the code

### load the library

library(meta)

library(metafor)

#### the model 
#### Freeman-Tukey Double arcsine transformation
#### Empirical Bayes estimator  and Hartung and Knapp adjustment

model <- metaprop(xi,ni,sm="PFT",hakn=TRUE, method.tau="EB")

########################
#
# subgroup analyses
#
########################


modelsub <- update(model, byvar=group)

summary(modelsub)

forest(modelsub,studlab=paste(study), print.byvar=FALSE)

#################################
#
# solution to a poor forest plot
#
#################################

### a good solution is to save the plot in .pdf 
### you have to play around with the 'width' and 'height' parameters 
### I used  width=12,height=13 (as higher the values, as more space you will get)

pdf(file="good forest plot.pdf", width=12,height=13)

forest(modelsub,studlab=paste(study), print.byvar=FALSE)

dev.off()

Meta分析：使用meta包进行汇总估算的森林图

1 个答案: