Wondering what the most effective way to determine event time in R is. Other answers seemed to not have grouping by ID, and that's a big chunk of what I need.
My data looks something like this:
time = rep(c(1:5),2)
id = c(rep(1,5),rep(2,5))
event = c(0,0,0,1,1,0,1,1,1,1)
df = data.frame(cbind(time,id,event))
df
time id event
1 1 1 0
2 2 1 0
3 3 1 0
4 4 1 1
5 5 1 1
6 1 2 0
7 2 2 1
8 3 2 1
9 4 2 1
10 5 2 1
>
Where "event" is binary observation (death of individual in experiment), and (should) remain 1 once it is first observed.
I need to determine the first time of event == 1, for each id number, and generate a vector of the id number and time first observed where event =1.
I originally was going to sloppily subset the data where event =1, and then just pick the minimum value of the week for each id, but that gets even sloppier when grouping by ID. Then I tried some aggregating but also struggled to do it across the ID grouping. I know tidyverse has some options but I'm a n00b.
I'm sure there's a very straightforward way to do this. Thanks!
The tidyverse is indeed super helpful for this kind of stuff.
df %>%
filter(event == 1) %>%
group_by(id) %>%
arrange(id, time) %>%
summarise(time = first(time)) %>%
ungroup()
# A tibble: 2 x 2
id time
<dbl> <dbl>
1 1 4
2 2 2