R 为每个受试者分配治疗
我有四个层(R 为每个受试者分配治疗,r,loops,R,Loops,我有四个层(stratum1,stratum2,stratum3,和stratum4),我希望在循环中为每个层执行此代码,并将变量添加到数据帧中 Strat1_Stratum1_Treat <- block_ra(blocks = ProjectData1$Stratum1, prob = .5, conditions = c("A","B")) Strat1\u Stratum1\u处理示例数据 如果您能分享最小数量的
stratum1
,stratum2
,stratum3
,和stratum4
),我希望在循环中为每个层执行此代码,并将变量添加到数据帧中
Strat1_Stratum1_Treat <- block_ra(blocks = ProjectData1$Stratum1,
prob = .5, conditions = c("A","B"))
Strat1\u Stratum1\u处理示例数据
如果您能分享最小数量的数据来重现问题,这将非常有帮助。请告诉我们您使用的软件包是什么。没有人知道函数block_ra
来自何处。太棒了,它工作得非常好
blocks <- sample(0:1, 40, TRUE)
data <- as.data.frame(matrix(blocks, 10, 4))
data
# V1 V2 V3 V4
# 1 0 1 1 1
# 2 0 0 0 0
# 3 1 1 0 1
# 4 0 0 0 1
# 5 1 1 1 1
# 6 1 1 0 1
# 7 0 0 0 0
# 8 1 0 0 0
# 9 0 0 1 0
# 10 0 0 0 0
data[5:8] <- lapply(data, block_ra, prob = .5, conditions = c("A", "B"))
data
# V1 V2 V3 V4 V1.1 V2.1 V3.1 V4.1
# 1 0 1 1 1 A A B B
# 2 0 0 0 0 B B B B
# 3 1 1 0 1 A A A A
# 4 0 0 0 1 B A B B
# 5 1 1 1 1 B B A A
# 6 1 1 0 1 A B B A
# 7 0 0 0 0 B A B A
# 8 1 0 0 0 B B A B
# 9 0 0 1 0 A A B A
# 10 0 0 0 0 A B A B