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Add factor levels to redcap_events col #211

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merged 4 commits into from
Nov 12, 2024
Merged

Add factor levels to redcap_events col #211

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c16a96a
Add factor levels and order to redcap_events col
rsh52 Nov 1, 2024
bd9c7aa
Update NEWS and version
rsh52 Nov 1, 2024
f335bf4
Undo reorder for review simplicity
rsh52 Nov 1, 2024
573caff
Remove ordered, fix tests
rsh52 Nov 12, 2024
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5 changes: 3 additions & 2 deletions DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
Package: REDCapTidieR
Type: Package
Title: Extract 'REDCap' Databases into Tidy 'Tibble's
Version: 1.2.0
Version: 1.2.1
Authors@R: c(
person("Richard", "Hanna", , "[email protected]", role = c("aut", "cre"),
comment = c(ORCID = "0009-0005-6496-8154")),
Expand Down Expand Up @@ -36,7 +36,8 @@ Imports:
pillar,
vctrs,
readr,
stats
stats,
forcats
Suggests:
covr,
knitr,
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1 change: 1 addition & 0 deletions NAMESPACE
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Expand Up @@ -66,6 +66,7 @@ importFrom(dplyr,select)
importFrom(dplyr,slice)
importFrom(dplyr,summarise)
importFrom(dplyr,ungroup)
importFrom(forcats,fct_inorder)
importFrom(formattable,percent)
importFrom(lobstr,obj_size)
importFrom(lubridate,is.Date)
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6 changes: 5 additions & 1 deletion NEWS.md
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@@ -1,4 +1,8 @@
# REDCapTidieR 1.2.0 (development version)
# REDCapTidieR 1.2.1 (development version)

- For longitudinal REDCap projects, the `redcap_events` column has been updated to give REDCap event factor levels and order for the `redcap_event` and `event_name` columns

# REDCapTidieR 1.2.0

- Added `combine_checkboxes()` analytics function
- Use `combine_checkboxes()` to consolidate multiple checkbox fields in a REDCap data tibble under a single column
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1 change: 1 addition & 0 deletions R/REDCapTidieR-package.R
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Expand Up @@ -8,6 +8,7 @@
#' left_join mutate pull recode relocate rename right_join row_number rowwise
#' select slice summarise ungroup coalesce cur_column bind_cols first nth n_distinct
#' first distinct
#' @importFrom forcats fct_inorder
#' @importFrom formattable percent
#' @importFrom lobstr obj_size
#' @importFrom lubridate is.difftime is.period is.POSIXt is.Date
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10 changes: 9 additions & 1 deletion R/read_redcap.R
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Expand Up @@ -177,7 +177,6 @@ read_redcap <- function(redcap_uri,
export_survey_fields <- ifelse(is.null(export_survey_fields), TRUE, export_survey_fields)

# Load REDCap Dataset output ----

db_data <- try_redcapr({
redcap_read_oneshot(
redcap_uri = redcap_uri,
Expand Down Expand Up @@ -463,12 +462,21 @@ add_event_mapping <- function(supertbl, linked_arms, repeat_event_types) {
event_info <- linked_arms

if (!is.null(repeat_event_types)) {
# Preserve factor levels post-join by referencing level order from linked_arms
repeat_event_types$redcap_event_name <- factor(repeat_event_types$redcap_event_name,
levels = levels(event_info$unique_event_name),
ordered = TRUE
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I would actually not make this ordered. We don't really know if the events in an arbitrary REDCap have meaningful order and using a plain factor will still preserve the order if they are meaningful.

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Well, for my purposes downstream in record_status_dashboard() creation I wanted to capture info on the order that events appear in the display. There's no real assumptions (to my knowledge) I can make otherwise when just accepting the supertibble. I believe the order that events come out resembles how they're ordered in the UI.

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Confirmed this will work using Prodigy as an example.

> db$redcap_events[[1]]
# A tibble: 1 × 5
  redcap_event      event_name        redcap_arm arm_name repeat_type 
  <ord>             <fct>             <chr>      <chr>    <chr>       
1 infusion_sequence Infusion Sequence 1          Arm 1    nonrepeating
> db$redcap_events[[1]]$event_name
[1] Infusion Sequence
23 Levels: Infusion Sequence Screening & Enrollment Manufacturing LD Chemo Pre-Infusion Infusion 1 Day Follow-Up ... Safety/Meds
> db$redcap_events[[1]]$event_name %>% levels()
 [1] "Infusion Sequence"      "Screening & Enrollment" "Manufacturing"          "LD Chemo"               "Pre-Infusion"          
 [6] "Infusion"               "1 Day Follow-Up"        "3 Day Follow-Up"        "7 Day Follow-Up"        "10 Day Follow-Up"      
[11] "14 Day Follow-Up"       "21 Day Follow-Up"       "28 Day Follow-Up"       "2 Month Follow-Up"      "3 Month Follow-Up"     
[16] "4 Month Follow-Up"      "5 Month Follow-Up"      "6 Month Follow-Up"      "9 Month Follow-Up"      "12 Month Follow-Up"    
[21] "Unscheduled"            "End of Study"           "Safety/Meds"

)

event_info <- event_info %>%
left_join(repeat_event_types, by = c("unique_event_name" = "redcap_event_name"))
}

event_info <- event_info %>%
add_partial_keys(.data$unique_event_name) %>%
mutate(
across(any_of("redcap_event"), ~ fct_inorder(redcap_event, ordered = TRUE))
) %>%
select(
redcap_form_name = "form", "redcap_event", "event_name", "redcap_arm", "arm_name", any_of("repeat_type")
) %>%
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6 changes: 5 additions & 1 deletion R/utils.R
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Expand Up @@ -162,7 +162,11 @@ link_arms <- function(redcap_uri,
)

left_join(db_event_instruments, arms, by = "arm_num") %>%
left_join(db_event_labels, by = c("arm_num", "unique_event_name"))
left_join(db_event_labels, by = c("arm_num", "unique_event_name")) %>%
mutate(
across(any_of("unique_event_name"), ~ fct_inorder(.x, ordered = TRUE)),
across(any_of("event_name"), ~ fct_inorder(.x, ordered = TRUE))
)
}

#' @title
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6 changes: 6 additions & 0 deletions tests/testthat/test-utils.R
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Expand Up @@ -228,6 +228,12 @@ test_that("link_arms works", {
# all arms are represented in output (test redcap has 2 arms)
n_unique_arms <- length(unique(out$arm_num))
expect_equal(n_unique_arms, 2)
expect_s3_class(out$unique_event_name, "ordered")
expect_s3_class(out$event_name, "ordered")
expect_equal(
levels(out$unique_event_name),
c("event_1_arm_1", "event_2_arm_1", "event_1_arm_2", "event_3_arm_2")
)
})

test_that("update_field_names works", {
Expand Down
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