For each participant, check, if an observation was expected, given the
PART_VARS
from item-level metadata
util_observation_expected(
rv,
study_data,
meta_data,
label_col = LABEL,
expected_observations = c("HIERARCHY", "ALL", "SEGMENT")
)
a vector with TRUE
or FALSE
for each row of study_data
, if for
study_data[rv]
a value is expected.
character the response variable, for that a value may be expected
study_data
meta_data
character mapping attribute colnames(study_data)
vs.
meta_data[label_col]
enum HIERARCHY | ALL | SEGMENT. How should
PART_VARS
be handled:
- ALL
: Ignore, all observations are
expected
- SEGMENT
: if PART_VAR
is 1, an
observation is expected
- HIERARCHY
: the default, if the
PART_VAR
is 1 for this variable and
also for all PART_VARS
of PART_VARS
up in the hierarchy, an observation is
expected.
Other missing_functions:
util_all_intro_vars_for_rv()
,
util_count_expected_observations()
,
util_filter_missing_list_table_for_rv()
,
util_get_code_list()
,
util_is_na_0_empty_or_false()
,
util_remove_empty_rows()
,
util_replace_codes_by_NA()