如何用R语言画森林图展示Logistic回归分析的结果

data(Affairs,package = "AER")df<-Affairsdf$ynaffairs<-ifelse(df$affairs>0,1,0)df$ynaffairs<-factor(df$ynaffairs,                     levels = c(0,1),                     labels = c("No","Yes"))fit.full<-glm(ynaffairs~gender+age+yearsmarried+                children+religiousness+education+occupation+rating,              data=df,family = binomial())fit.result<-summary(fit.full)df1<-fit.result$coefficientsdf2<-confint(fit.full)df3<-cbind(df1,df2)df4<-data.frame(df3[-1,c(1,4,5,6)])df4$Var<-rownames(df4)colnames(df4)<-c("OR","Pvalue","OR_1","OR_2","Var")df5<-df4[,c(5,1,2,3,4)]df5$OR_mean<-df5$ORdf5$OR<-paste0(round(df5$OR,2),               "(",               round(df5$OR_1,2),               "~",               round(df5$OR_2,2),               ")")df5$Pvalue<-round(df5$Pvalue,3)write.csv(df5,file = "forestplot_example.csv",          quote = F,row.names = F)

install.packages("forestplot")

library(forestplot)fp<-read.csv("forestplot_example.csv",header=T)forestplot(labeltext=as.matrix(fp[,1:3]),           mean=fp$OR_mean,           lower=fp$OR_1,           upper=fp$OR_2,           zero=0,           boxsize=0.2,           graph.pos=2)

forestplot(labeltext=as.matrix(fp[,1:3]),           mean=fp$OR_mean,           lower=fp$OR_1,           upper=fp$OR_2,           zero=0,           boxsize=0.2,           lineheight = unit(7,'mm'),           colgap=unit(2,'mm'),           lwd.zero=1.5,           lwd.ci=2,            col=fpColors(box='#458B00',                        summary='#8B008B',                        lines = 'black',                        zero = '#7AC5CD'),           xlab="OR",           lwd.xaxis =1,           txt_gp = fpTxtGp(ticks = gpar(cex = 0.85),                            xlab  = gpar(cex = 0.8),                            cex = 0.9),           lty.ci = "solid",           title = "Forestplot",            line.margin = 0.08,           graph.pos=2)