按唯一ID为组填写缺失数据 [英] fill in missing data for group by unique ID

问题描述

我的临床数据结构如下所示:

My clinical data structure looks like this:

patientid <- c(100,100,100,101,101,101,102,102,102,104,104,104)
group <- c(1,1,NA,2,NA,NA,1,1,1,2,2,NA)

Data<- data.frame(patientid=patientid,group=group)

如果缺少数据，则 NA 应与同一患者 ID 的其他组值相同.换句话说，患者总是在同一组中，需要填写缺失的数据以反映这一点.所以它应该是这样的:

If there is missing data then the NA should become the same value as the other group value for the same patient id. In other words a patient is always in the same group and the missing data needs to be filled in to reflect that. So it should look like this:

patientid <- c(100,100,100,101,101,101,102,102,102,104,104,104)
group <- c(1,1,1,2,2,2,1,1,1,2,2,2)

Data<- data.frame(patientid=patientid,group=group)

推荐答案

你可以写一个小辅助函数，如:

You can write a little helper function like:

fun <- function(x) replace(x, is.na(x), x[!is.na(x)][1])

然后，您可以在 base R 中的 transform 或 within 中使用它:

Then, you can use it in transform or within in base R:

transform(Data, group = ave(group, patientid, FUN = fun))
#    patientid group
# 1        100     1
# 2        100     1
# 3        100     1
# 4        101     2
# 5        101     2
# 6        101     2
# 7        102     1
# 8        102     1
# 9        102     1
# 10       104     2
# 11       104     2
# 12       104     2

甚至与其他包:

library(data.table)
as.data.table(Data)[, group := fun(group), patientid][]

即使组值不是每个患者patientid"的第一个值，这也将起作用.试试，例如:

This will work even if the group value is not the first value for each patient "patientid". Try, for example:

# First row of "group" is `NA`
Data <- Data[c(3, 1, 2, 4:nrow(Data)), ]

这篇关于按唯一ID为组填写缺失数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！