I have a similar problem like this one: How can I create a dummy variable over consecutive values by group id?
the difference is: as soon I have the Dummy = 1 I want my dummy for the rest of my group (ID) beeing 1 since year is in descending order. So for example, out of df1:
df1 <-data.frame(ID = rep(seq(1:3), each = 4),
year = rep(c(2014, 2015, 2016, 2017),3),
value = runif(12, min = 0, max = 25),
Dummy = c(0,0,1,0 ,0,1,0,1, 1,0,0,0))
shall be :
df2 <- data.frame(ID = rep(seq(1:4), 3),
year = rep(c(2014, 2015, 2016, 2017),3),
value = runif(12, min = 0, max = 25),
Dummy = c(0,0,1,1 ,0,1,1, 1, 1,1,1,1))
I've tried something like that (and some others) but that failed:
df2<- df1%>% group_by(ID) %>% arrange(ID , year) %>%
mutate(treated = case_when(Dummy == 1 ~ 1,
lag(Dummy, n= unique(n()), default = 0) == 1 ~ 1))
If your input data is as below then we can just use cummax():
library(dplyr)
df1 <-data.frame(ID = rep(seq(1:3), each = 4),
year = rep(c(2014, 2015, 2016, 2017),3),
value = runif(12, min = 0, max = 25),
Dummy = c(0,0,1,0 ,0,1,0,1, 1,0,0,0))
df1
#> ID year value Dummy
#> 1 1 2014 14.144996 0
#> 2 1 2015 20.621603 0
#> 3 1 2016 8.325170 1
#> 4 1 2017 21.725028 0
#> 5 2 2014 11.894383 0
#> 6 2 2015 13.445744 1
#> 7 2 2016 3.332338 0
#> 8 2 2017 2.984941 1
#> 9 3 2014 17.551266 1
#> 10 3 2015 5.250556 0
#> 11 3 2016 11.062577 0
#> 12 3 2017 20.169439 0
df1 %>%
group_by(ID) %>%
mutate(Dummy = cummax(Dummy))
#> # A tibble: 12 x 4
#> # Groups: ID [3]
#> ID year value Dummy
#> <int> <dbl> <dbl> <dbl>
#> 1 1 2014 14.1 0
#> 2 1 2015 20.6 0
#> 3 1 2016 8.33 1
#> 4 1 2017 21.7 1
#> 5 2 2014 11.9 0
#> 6 2 2015 13.4 1
#> 7 2 2016 3.33 1
#> 8 2 2017 2.98 1
#> 9 3 2014 17.6 1
#> 10 3 2015 5.25 1
#> 11 3 2016 11.1 1
#> 12 3 2017 20.2 1
Created on 2022-10-14 by the reprex package (v2.0.1)