Standardized warning system

When checking your data, filter your dataset to get only problematic rows.
Then, use either:

• edc_data_warn() to generate a standardized warning that can be forwarded to the datamanager

• edc_data_warn() to abort the script if the problem is too serious

Database issues should be traced in a separate file, each with an identifying row number, and the file should be shared with the data-manager.
Use edc_data_warnings() to generate the table for such a file.

Usage

edc_data_warn(
  df,
  message,
  ...,
  issue_n = "xx",
  max_subjid = 5,
  write_to_csv = FALSE,
  col_subjid = get_subjid_cols()
)

edc_data_stop(...) #same arguments

edc_data_warnings()

Arguments

df

the filtered dataframe

message

the message. Can use cli formats.

...

unused

issue_n

identifying row number

max_subjid

max number of subject ID to show in the message

write_to_csv

a path to save df in a csv file that can be shared with the DM for more details.

col_subjid

column name for subject ID. Set to NULL to ignore.

Value

df invisibly

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
tm = edc_example()
#> Warning: Option "edc_lookup" has been overwritten.
load_list(tm)
db0 %>% 
  filter(age>70) %>% 
  edc_data_warn("Age should not be >70", issue_n=1)
#> Warning: Issue #01: Age should not be >70 (2 patients: #9 and #12)

db0 %>% 
  filter(age<25) %>% 
  edc_data_warn("Age should not be <25", issue_n=2)
#> Warning: Issue #02: Age should not be <25 (1 patient: #18)

db1 %>% 
  filter(n()>1, .by=SUBJID) %>% 
  edc_data_warn("There are duplicated patients in `db1`", issue_n=3)
#> Warning: Issue #03: There are duplicated patients in `db1` (50 patients: #1, #2, #3, #4,
#> #5, …)

edc_data_warnings()
#> # A tibble: 3 × 4
#>   issue_n message                                subjid     fun     
#>   <chr>   <chr>                                  <list>     <chr>   
#> 1 01      Age should not be >70                  <chr [2]>  cli_warn
#> 2 02      Age should not be <25                  <chr [1]>  cli_warn
#> 3 03      There are duplicated patients in `db1` <chr [50]> cli_warn

if (FALSE) { # \dontrun{
db0 %>% 
  filter(age<25) %>% 
  edc_data_warn("Age should not be <25", write_to_csv="check/check_age_25.csv")
  
db0 %>% 
  filter(age<25) %>% 
  edc_data_stop("Age should *never* be <25")
} # }