如何在具有百分比差异的森林地块上放置置信区间

Question

我被困在如何将 CI 放在森林地块上，并且我可以找到 p 值。 我找到了我正在使用的这段代码（附在下面），但它没有给我 CI。

forest.rma(SMD.ma) # 这里总结了使用一个 forrest plot function 的 metafor package 的结果。 它是可选的，因为它看起来很丑。

                                   # Presenting results in Grpahs
                theme_set(theme_bw(base_size=10))  
                forrest_data <-rbind(data.frame(ES=ROM.ma$yi,SE=sqrt(ROM.ma$vi), Type="Study", Study=DataA$Manure_rate), data.frame(ES=ROM.ma$b,SE=ROM.ma$se,Type="Summary",Study="SUMMARY")) # Update "Manure_rate"
                forrest_data$Study2<-factor(forrest_data$Study )  #, levels=rev(levels(forrest_data$Study))
                                                                                                                                              
                forrest_data$Percent <- (exp(forrest_data$ES)-1)*100 # creating new column for the percent of effect size
                Data_ordored <- forrest_data %>% group_by(Study2) %>% summarize(Percent2 = mean(Percent))   # Creating a new dataset grouping sub-group by their mean value of percent 
                Data_ordored$Love<- "Crop yield Meta-analysis"       # Trick done to insert a sub-title during a pseudo-ggplot wrapping. #Update label
                df <- data.frame (Study2= "SUMMARY", Percent2= 106)  # Trick done to insert a single indicative point. #Update Percent2
            

               plot1 <- ggplot(Data_ordored, aes(x=reorder(Study2, Percent2),y=Percent2)) +
                 
                 geom_segment(aes(xend = Study2, yend = 0, colour=Percent2), size = 1.2)+
                 geom_point(size = 4, shape=21, fill="black" ) + 
                 geom_label(aes(Study2, Percent2+1.6, label = signif(Percent2, 2)), colour = "darkred", nudge_x = 0.35, size = 3)+           
                 labs(y= "PERCENTAGE IMPACT (%)", x="MANURE APPLICATION RATES") +coord_flip() + theme( legend.justification="top", legend.position = "right")  + # Update xlabel
                 scale_colour_gradient2(low='blue', mid = "white", high='red', midpoint = 220, name="Impact gradient(%)") +  # Update midpoint
                 stat_summary(data = df, fun=max, geom="point",  size=8, color = 'green', fill="green", aes(shape = 'Overall Effect')) +
                 scale_shape_manual('Standardized Impact', values = c(21) ) +
                 facet_wrap(~ Love)