用于纵向数据的R条件变量

Question

I have data for each month for a year on insured people. All variables are dummy variables and I need to create a new variable that shows when a person became uninsured. I am calling the variable duration. My dataset (df) looks something like this:

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

101 1 1 1 1 0 0 1 1 1 1 1 1

102 1 1 1 1 0 0 0 0 0 0 0 0

103 1 1 1 1 1 1 1 1 1 1 1 1

104 1 1 1 1 0 1 1 0 1 1 1 1

In the dataset, 1 is insured and 0 is uninsured.My new variable would have the have the col position for when the person changed from 1 to 0. For instance in the first row, my variable duration would have the value 5 for may. I am only insterested in the first instance of 0. For example, in row 4, i only need 5 for may and can ignore august. Also, if the person does not become uninsured like in the case of 103, the new variable would just have the value "0".

I began by using ifelse statement below but it would take me a lot of time to keep repeating it. if you have an easier solution for this, please share. Thanks!

df$duration=ifelse(df$feb==1,0,2)

Answer 1

Another idea that seems valid:

tmp = !DF[-1]
max.col(tmp, "first") * as.logical(rowSums(tmp))
#[1] 5 5 0 5

Where

DF = structure(list(ID = 101:104, Jan = c(1L, 1L, 1L, 1L), Feb = c(1L, 
1L, 1L, 1L), Mar = c(1L, 1L, 1L, 1L), Apr = c(1L, 1L, 1L, 1L), 
    May = c(0L, 0L, 1L, 0L), Jun = c(0L, 0L, 1L, 1L), Jul = c(1L, 
    0L, 1L, 1L), Aug = c(1L, 0L, 1L, 0L), Sep = c(1L, 0L, 1L, 
    1L), Oct = c(1L, 0L, 1L, 1L), Nov = c(1L, 0L, 1L, 1L), Dec = c(1L, 
    0L, 1L, 1L)), .Names = c("ID", "Jan", "Feb", "Mar", "Apr", 
"May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"), class = "data.frame", row.names = c(NA, 
-4L))

Answer 2

There are more efficient alternatives, but maybe this is sufficient:

apply(DF[,-1], 1, function(x) which(x==0)[1])
#[1]  5  5 NA  5