在R中的不平衡面板数据中创建滞后变量 [英] Create lagged variable in unbalanced panel data in R

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问题描述

我想创建一个变量,其中包含组内前一年的变量值。

  id日期值
1 1 1992 4.1
2 1 NA 4.5
3 1 1991 3.3
4 1 1990 5.3
5 1 1994 3.0
6 2 1992 3.2
7 2 1991 5.2

value_lagged 应在组内缺少上一年时丢失 - 因为它是组内的第一个日期如在行4,7中),或者因为在数据中存在年差距(如在行5中)。此外,当缺少当前时间(如第2行中所示)时,应缺少 value_lagged



  id日期值value_lagged 
1 1 1992 4.1 3.3
2 1 NA 4.5 NA
3 1 1991 3.3 5.3
4 1 1990 5.3 NA
5 1 1994 3.0 NA
6 2 1992 3.2 5.2
7 2 1991 5.2 NA






现在,在R中,我使用 data.table package

  DT = data.table(id = c(1,1,1,1,1) ,2,2),
date = c(1992,NA,1991,1990,1994,1992,1991),
value = c(4.1,4.5,3.3,5.3,3.0,3.2,5.2 )

setkey(DT,id,date)
DT [,value_lagged:= DT [J(id,date-1),value],]
DT [ .na(date),value_lagged:= NA,]

我。我想知道是否有更好的选择使用 data.table dplyr 或任何其他包。非常感谢!






Stata

  tsset id date 
gen value_lagged = L.value
pre>

解决方案

在组内使用函数 tlag id

定义

  tlag < n = 1L,time){
index < - match(time-n,time,incomparable = NA)
x [index]
}

df%> ;%group_by(id)%>%mutate(value_lagged = tlag(value,1,time = date))


I'd like to create a variable containing the value of a variable in the previous year within a group.

     id   date        value
1     1   1992          4.1  
2     1     NA          4.5  
3     1   1991          3.3  
4     1   1990          5.3  
5     1   1994          3.0  
6     2   1992          3.2  
7     2   1991          5.2  

value_lagged should be missing when the previous year is missing within a group - either because it is the first date within a group (as in row 4, 7), or because there are year gaps in the data (as in row 5). Also, value_lagged should be missing when the current time is missing (as in row 2).

This gives:

     id   date    value    value_lagged  
1     1   1992      4.1             3.3
2     1     NA      4.5              NA
3     1   1991      3.3             5.3
4     1   1990      5.3              NA
5     1   1994      3.0              NA
6     2   1992      3.2             5.2
7     2   1991      5.2              NA


For now, in R, I use the data.table package

 DT = data.table(id    = c(1,1,1,1,1,2,2),
                 date  = c(1992,NA,1991,1990,1994,1992,1991),
                 value = c(4.1,4.5,3.3,5.3,3.0,3.2,5.2)
                )
 setkey(DT, id, date)
 DT[, value_lagged := DT[J(id, date-1), value], ]
 DT[is.na(date), value_lagged := NA, ]

It's fast but it seems somewhat error prone to me. I'd like to know if there are better alternatives using data.table, dplyr, or any other package. Thanks a lot!


In Stata, one would do:

    tsset id date
    gen value_lagged=L.value

解决方案

Using a function tlag within groups defined by id

tlag <- function(x, n = 1L, time) { 
  index <- match(time - n, time, incomparables = NA)
  x[index]
}

df %>% group_by(id) %>% mutate(value_lagged = tlag(value, 1, time = date))

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