Converts a list of REDCap data frames from long to wide format. Handles longitudinal projects, but not yet repeated instruments.
Usage
redcap_wider(
data,
event.glue = "{.value}_{redcap_event_name}",
inst.glue = "{.value}_{redcap_repeat_instance}"
)Arguments
- data
A list of data frames.
- event.glue
A dplyr::glue string for repeated events naming
- inst.glue
A dplyr::glue string for repeated instruments naming
Examples
# Longitudinal
list1 <- list(
data.frame(
record_id = c(1, 2, 1, 2),
redcap_event_name = c("baseline", "baseline", "followup", "followup"),
age = c(25, 26, 27, 28)
),
data.frame(
record_id = c(1, 2),
redcap_event_name = c("baseline", "baseline"),
gender = c("male", "female")
)
)
redcap_wider(list1)
#> Joining with `by = join_by(record_id)`
#> record_id age_baseline age_followup gender
#> 1 1 25 27 male
#> 2 2 26 28 female
# Simpel with two instruments
list2 <- list(
data.frame(
record_id = c(1, 2),
age = c(25, 26)
),
data.frame(
record_id = c(1, 2),
gender = c("male", "female")
)
)
redcap_wider(list2)
#> Joining with `by = join_by(record_id)`
#> record_id age gender
#> 1 1 25 male
#> 2 2 26 female
# Simple with single instrument
list3 <- list(data.frame(
record_id = c(1, 2),
age = c(25, 26)
))
redcap_wider(list3)
#> record_id age
#> 1 1 25
#> 2 2 26
# Longitudinal with repeatable instruments
list4 <- list(
data.frame(
record_id = c(1, 2, 1, 2),
redcap_event_name = c("baseline", "baseline", "followup", "followup"),
age = c(25, 26, 27, 28)
),
data.frame(
record_id = c(1, 1, 1, 1, 2, 2, 2, 2),
redcap_event_name = c(
"baseline", "baseline", "followup", "followup",
"baseline", "baseline", "followup", "followup"
),
redcap_repeat_instrument = "walk",
redcap_repeat_instance = c(1, 2, 1, 2, 1, 2, 1, 2),
dist = c(40, 32, 25, 33, 28, 24, 23, 36)
),
data.frame(
record_id = c(1, 2),
redcap_event_name = c("baseline", "baseline"),
gender = c("male", "female")
)
)
redcap_wider(list4)
#> Joining with `by = join_by(record_id)`
#> Joining with `by = join_by(record_id)`
#> record_id age_baseline age_followup dist_1_baseline dist_1_followup
#> 1 1 25 27 40 25
#> 2 2 26 28 28 23
#> dist_2_baseline dist_2_followup gender
#> 1 32 33 male
#> 2 24 36 female