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Describes each problem in the rule's own words, worst first, with the rows and values that caused it. A whole-study result is grouped by dataset, with a summary first, so you can see where the trouble is before reading detail.

Usage

# S3 method for class 'coreval_result'
print(x, n = 10, rows = 3, guidance = FALSE, ...)

Arguments

x

A result from check_dataset() or check_study().

n

Maximum problems to describe - per dataset, for a study result. The rest are counted, not listed. Default 10.

rows

Maximum example records to show per problem. Default 3.

guidance

Also print the sentence from the Implementation Guide that each rule enforces - the "why" behind it. Off by default: it roughly doubles the length of the report.

...

Ignored.

Value

x, invisibly.

Examples

ae <- data.frame(
  STUDYID = "S1", DOMAIN = "AE", USUBJID = c("01", "01"),
  AESEQ = c(1, 2), AETERM = c("Headache", "Rash"),
  AESTDTC = c("2024-01-10", "2024-02-30")
)
check_dataset(ae)
#> 
#> ── coreval — AE ────────────────────────────────────────────────────────────────
#> 
#> 4 problems across 2 records  (160 checks ran)
#> 
#>   wrong value         2   the data breaks the rule - start here
#>   missing required    1   the standard requires it
#>   missing optional    1   often legitimate: not collected, screen failure, ...
#> 
#> [wrong value]
#> The Study Day of Start of Observation (--STDY) is not present in the dataset
#>   when Start Date/Time of Observation (--STDTC) is present.
#>   1 record · AESTDTC
#>     AESTDTC = "2024-01-10"
#>     CORE-000328  · also FB3202
#> 
#> [wrong value]
#> Variable value is not in correct ISO 8601 date or datetime format
#>   1 record · AESTDTC
#>     row 2     AESTDTC = "2024-02-30"
#>     CORE-000547  · also SEND66, SEND67, SEND68, ...
#> 
#> [missing required]
#> At least one required variable is missing from dataset
#>   1 record
#>     missing required variables: AEDECOD
#>     CORE-000355  · also CG0014, SEND12, TIG0299, ...
#> 
#> [missing optional]
#> At least one expected variable is missing from dataset
#>   1 record
#>     missing expected variables: AELLT, AELLTCD, AEPTCD, AEHLT, AEHLTCD, AEHLGT, AEHLGTCD, AEBODSYS, ...
#>     CORE-000334  · also CG0016, TIG0301, SEND13, ...
#> 
#> ────────────────────────────────────────────────────────────────────────────────
#> 51 checks could not run.
#>   25 need other datasets (DM, POOLDEF, SUPPAE, SV, TA, TO, ...)
#>      → run check_study() on the whole folder to cover these
#>   16 ask what the whole study contains
#>   6 need a define.xml
#>   4 for other reasons, see result$skipped
#> 
#> No standard declared, so rules from every standard ran.
#>   Narrow with  standard = "SDTMIG"  (or "SENDIG", "TIG", ...)
#> 
#> Fix what you can, then run this again.
#> To track the rest:  write_findings(result, "issues.xlsx")