How to identify duplicate items within a subset of data - r

Question

I am trying to identify which trials, within a long form dataset, are repeated but only within certain blocks per participant. My data is structured something like this:
sub block trial item
1 1 1 A
1 1 2 B
1 2 1 A
1 2 2 B
1 3 1 B
1 3 2 C
2 1 1 A
2 1 2 B
2 2 1 A
2 2 2 B
2 3 1 B
2 3 2 C
What I would like to create is a new column that indicates for each participant, which items are repeating and another new column with a new trial code, but only if the items are repeated in blocks 2 and 3. So it would look something like this:
sub block trial item dup newtrial
1 1 1 A FALSE 1
1 1 2 B FALSE 2
1 2 1 A FALSE 1
1 2 2 B FALSE 2
1 3 1 C FALSE 1
1 3 2 B TRUE 102
2 1 1 A FALSE 1
2 1 2 B FALSE 2
2 2 1 A FALSE 1
2 2 2 B FALSE 2
2 3 1 C FALSE 1
2 3 2 B TRUE 102
I have been able to identify duplicates across the whole dataset and add 100 to each trial number using the following code:
data$dup<-duplicated(data$item)
data$newtrial<-NA
data<-transform(data,
item=make.unique(as.character(item)),
newtrial=ifelse(duplicated(item),trial+100, trial))
What I have not been able to figure out is how to constrain the function to each individual subject and only certain blocks within each subject number.
Thanks!

Answer 1

another option using data.table:
library(data.table)
xt <- fread("sub block trial item
1 1 1 A
1 1 2 B
1 2 1 A
1 2 2 B
1 3 1 B
1 3 2 B
2 1 1 A
2 1 2 B
2 2 1 A
2 2 2 B
2 3 1 B
2 3 2 B")
xt[,
c("dup","ntrial") := {
dup <- duplicated(item)
tt <- ifelse(dup,trial+100L,trial)
list(dup,tt)
},"sub,block"]

Answer 2

You can do this using dplyr grouping the observations by sub and block:
library(dplyr)
res <- data %>% group_by(sub,block) %>%
mutate(dup=duplicated(item)) %>%
ungroup %>%
mutate(newtrial=ifelse(dup,trial+100,trial))
We use mutate to create new columns dup and newtrial.
Data: Modifying your data slightly to introduce duplicate item for sub=1, block=3 and sub=2, block=3:
data <- structure(list(sub = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L), block = c(1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L,
3L), trial = c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L
), item = structure(c(1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L,
2L, 2L), .Label = c("A", "B"), class = "factor")), .Names = c("sub",
"block", "trial", "item"), class = "data.frame", row.names = c(NA,
-12L))
## sub block trial item
##1 1 1 1 A
##2 1 1 2 B
##3 1 2 1 A
##4 1 2 2 B
##5 1 3 1 B
##6 1 3 2 B
##7 2 1 1 A
##8 2 1 2 B
##9 2 2 1 A
##10 2 2 2 B
##11 2 3 1 B
##12 2 3 2 B
Using this data:
print(res)
### A tibble: 12 x 6
## sub block trial item dup newtrial
## <int> <int> <int> <fctr> <lgl> <dbl>
##1 1 1 1 A FALSE 1
##2 1 1 2 B FALSE 2
##3 1 2 1 A FALSE 1
##4 1 2 2 B FALSE 2
##5 1 3 1 B FALSE 1
##6 1 3 2 B TRUE 102
##7 2 1 1 A FALSE 1
##8 2 1 2 B FALSE 2
##9 2 2 1 A FALSE 1
##10 2 2 2 B FALSE 2
##11 2 3 1 B FALSE 1
##12 2 3 2 B TRUE 102