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Normalisation dictionary for participant metadata

Source: R/participants.R
sdt_participant_dictionary.Rd

The TDSC participant register stores four covariates as German free text. This function holds the maps that fold that text onto controlled vocabularies as data, so extending the package for a spelling it has not seen is one argument rather than a code change: whatever you pass is utils::modifyList()-merged, recursively, onto the shipped default.

Usage

sdt_participant_dictionary(
  funktion = NULL,
  titel = NULL,
  fachbereich = NULL,
  anrede = NULL
)

Arguments

funktion, titel, fachbereich, anrede

Optional named lists merged onto the corresponding shipped slot. Each slot has a map (normalised key to level), and, depending on the covariate, patterns, levels, score and group. Adding one spelling means passing funktion = list(map = list("leitender oberarzt" = "consultant")).

Value

An S3 object of class sdt_participant_dictionary: a list of four slots, with print() and format() methods.

Details

The four vocabularies are:

  • funktion — an ordered seniority ladder, resident < specialist < consultant < chief (Assistenzarzt, Facharzt, Oberarzt, Chefarzt), scored 1–4. other ("Andere") is a real answer that sits off the ladder and scores NA; not_stated ("Nichts angegeben") is a declared non-answer and is treated as missing, not as a sixth grade.

  • titel — the academic ladder none < doctorate < habilitation < professor, scored 0–3. Matching is exact on a punctuation- and case-insensitive key first, then falls back to patterns, where every rung is tested and the highest match wins. An empty title box is filled with none when blank_is_none is TRUE — and every filled row is flagged, see sdt_read_participants().

  • fachbereich — a controlled specialty list plus a surgical / non-surgical group. Multi-specialty free text ("Chirurgie, Unfallchirurgie") is collapsed by the stated rule the primary specialty is the one mentioned first: the pattern whose match starts earliest in the string wins.

  • anrede — salutation to sex. This is a proxy: it records how a person was addressed on a registration form, not a gender identity.

See also

sdt_read_participants(), which applies it.

Examples

d <- sdt_participant_dictionary()
d
#> <sdt_participant_dictionary>
#> funktion    6 spellings -> resident < specialist < consultant < chief
#> titel       22 spellings + 3 patterns -> none < doctorate < habilitation < professor
#> fachbereich 14 spellings -> 11 specialties (6 surgical)
#> anrede      female / male (a salutation proxy, not gender identity)
d$funktion$score
#>   resident specialist consultant      chief 
#>          1          2          3          4 

# One new spelling, no package patch.
d2 <- sdt_participant_dictionary(
  funktion = list(map = list("leitender oberarzt" = "consultant"))
)
d2$funktion$map[["leitender oberarzt"]]
#> [1] "consultant"