R function to change value after a condition has been fulfilled

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Participants in an experiment took a test that has a rule that says "once a participant has gotten 6 items wrong in a window of 8 items, you stop running the test". However, some experimenters kept testing past this point. I now need to find a way in which I can automatically see where the test should have been stopped, and change all values following the end to 0 (= item wrong). I am not even sure if this is something that can be done in R.

To be clear, I would like to go row by row (which are the participants) and once there are six 0s in a given window of 8 columns (items), I would need all values after the sixth 0 to be 0 too.

While the reproducible data is below, here is a visualization of what I would need, where the blue cells are the ones that should change to 0:

Pre-changes Post-changes

Reproducible data:

structure(list(Participant_ID = c("E01P01", "E01P02", "E01P03", 
"E01P04", "E01P05", "E01P06", "E01P07", "E01P08", "E02P01", "E02P02"
), A2 = c(1, 1, 1, 0, 0, 1, 1, 1, 1, 1), A3 = c(1, 1, 0, 0, 0, 
1, 0, 0, 0, 0), B1 = c(1, 1, 1, 0, 0, 1, 0, 0, 1, 1), B2 = c(1, 
1, 1, 1, 1, 1, 0, 0, 0, 1), C3 = c(1, 0, 0, 1, 0, 1, 0, 0, 0, 
1), C4 = c(1, 0, 0, 0, 0, 1, 0, 0, 1, 1), D1 = c(1, 0, 0, 0, 
0, 1, 0, 0, 0, 0), D3 = c(1, 1, 1, 1, 0, 0, 1, 0, 0, 1), E1 = c(1, 
0, 0, 0, 0, 1, 0, 0, 0, 1), E3 = c(1, 1, 0, 1, 0, 1, 0, 0, 0, 
0), F1 = c(1, 0, 0, 0, 1, 0, 0, 1, 0, 0), F4 = c(1, 1, 1, 1, 
0, 1, 0, 1, 1, 0), G1 = c(1, 0, 0, 0, 0, 1, 0, 0, 0, 1), G2 = c(0, 
0, 0, 0, 1, 1, 1, 0, 1, 1)), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame"))

Any help is highly appreciated!

r
1 Answers

Here is a solution that involves some pivoting, rollsum, cumsum, if_else logic, then pivoting back. Let me know if it works.

library(tidyverse)
library(zoo)

structure(list(Participant_ID = c("E01P01", "E01P02", "E01P03", 
"E01P04", "E01P05", "E01P06", "E01P07", "E01P08", "E02P01", "E02P02"
), A2 = c(1, 1, 1, 0, 0, 1, 1, 1, 1, 1), A3 = c(1, 1, 0, 0, 0, 
1, 0, 0, 0, 0), B1 = c(1, 1, 1, 0, 0, 1, 0, 0, 1, 1), B2 = c(1, 
1, 1, 1, 1, 1, 0, 0, 0, 1), C3 = c(1, 0, 0, 1, 0, 1, 0, 0, 0, 
1), C4 = c(1, 0, 0, 0, 0, 1, 0, 0, 1, 1), D1 = c(1, 0, 0, 0, 
0, 1, 0, 0, 0, 0), D3 = c(1, 1, 1, 1, 0, 0, 1, 0, 0, 1), E1 = c(1, 
0, 0, 0, 0, 1, 0, 0, 0, 1), E3 = c(1, 1, 0, 1, 0, 1, 0, 0, 0, 
0), F1 = c(1, 0, 0, 0, 1, 0, 0, 1, 0, 0), F4 = c(1, 1, 1, 1, 
0, 1, 0, 1, 1, 0), G1 = c(1, 0, 0, 0, 0, 1, 0, 0, 0, 1), G2 = c(0, 
0, 0, 0, 1, 1, 1, 0, 1, 1)), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame")) %>%
  as_tibble() %>%
  pivot_longer(-1) %>%
  group_by(Participant_ID) %>%
  mutate(running_total = zoo::rollsumr(value==0, k = 8, fill = 0),
         should_terminate = cumsum(running_total >= 6),
         value = if_else(should_terminate > 0, 0, value)) %>%
  ungroup() %>%
  select(Participant_ID, name, value) %>%
  pivot_wider(names_from = name, values_from = value)
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