Populate the provided cdi data with percentile values for that specific age, instrument_type, measure and language. Loosely based on the work from this repo https://github.com/kachergis/cdi-percentiles/tree/main by George Kachergis and Jess Mankewitz with advice from Virginia Marchman.

populate_cdi_percentiles(subjects_table)

Arguments

subjects_table: a subjects table with unnested cdi data, needs columns "subject_id", "language", "instrument_type", "age", "sex", "measure", "rawscore"

Value

the input table with added columns containing the reference age used, the reference year used, and both gender specific and general percentile values for the cdi score

Examples

# \donttest{
full_cdi_data <- all_subjects %>%
  unnest(subject_aux_data) %>%
  filter(!is.na(cdi_responses)) %>%
  unnest(cdi_responses) %>%
  peekbankr::cleanup_cdi_data() %>%
  peekbankr::populate_cdi_percentiles()
#> Error in all_subjects %>% unnest(subject_aux_data) %>% filter(!is.na(cdi_responses)) %>%     unnest(cdi_responses) %>% peekbankr::cleanup_cdi_data() %>%     peekbankr::populate_cdi_percentiles(): could not find function "%>%"
# }