EDCimport (version 0.6.0)

edc_data_warn: Standardized warning system

Description

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_stop() to abort the script if the problem is too serious.

Each time edc_data_warn is used, the warning is saved internally so that a summary of all your warnings can be retrieved using edc_data_warnings.
The result can be saved into an Excel file using save_edc_data_warnings().

Usage

edc_data_warn(
  df,
  message,
  ...,
  issue_n = "xx",
  max_subjid = 5,
  csv_path = FALSE,
  envir = parent.frame(),
  col_subjid = get_subjid_cols()
)
edc_data_stop(df, message, ..., issue_n, max_subjid, csv_path, envir, col_subjid)
edc_data_warnings()

Value

df invisibly

Arguments

df

the filtered dataframe

message

the message. Can use cli formats. df can be accessed using the .data special keyword (see example)

...

unused

issue_n

identifying row number

max_subjid

max number of subject ID to show in the message

csv_path

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

envir

the environment to evaluate message in.

col_subjid

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

Examples

library(dplyr)
db = edc_example()
load_database(db)
enrol %>% 
  filter(age>70) %>% 
  edc_data_warn("Age should not be >70", issue_n=1)

enrol %>% 
  filter(age<25) %>% 
  edc_data_warn("Age should not be <25", issue_n=2)

data1 %>% 
  filter(n()>1, .by=subjid) %>% 
  edc_data_warn("There are duplicated patients in `data1` ({nrow(.data)} rows)", issue_n=3)

enrol %>% 
  filter(age<25) %>% 
  edc_data_warn("Age should not be <25", issue_n=NULL)
  
edc_data_warnings()

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