{代码碎片}

#保留三位小数
options(scipen = 999)

　　

#删除数据不全的样本
aa <- na.omit(aa)

　　

#删掉某些列
aa<-aa[,-c(8:10)]

　　

#取分组变量为特定值的建立子集
aa <- subset(bio, diagnosis == "0" | diagnosis == "2")

　　

#只要某些变量纳入分析
aa <- data[, c("age", "MD_Prog","vf_md_baseline","VF.over.cutoff","G_stage","past_his_1","past_his_2",
               "eye_his_4","vfi_baseline","cct_baseline","dh","drug_change","vcdr_baseline")]

　　

#按照某个连续变量设立分层标签
as$CCT_group <- cut(as$CCT, breaks=c(435,530,550,570,645), labels=c("A","B","C","D"))

　　

#整理变量类型
for (i in names(aa)[c(4,7:33)]){aa[,i] <- as.factor(aa[,i])}
aa[,39]<-as.numeric(aa[,39])
aa[,19]<-as.integer(aa[,19])