Returns a data frame of subject events with missing values.
missingSummary(
rcon,
excludeMissingForms = TRUE,
...,
fixed_fields = REDCAP_SYSTEM_FIELDS
)# S3 method for redcapApiConnection
missingSummary(
rcon,
excludeMissingForms = TRUE,
...,
fixed_fields = REDCAP_SYSTEM_FIELDS,
exportRecordsArgs = list(),
error_handling = getOption("redcap_error_handling"),
config = list(),
api_param = list()
)
missingSummary_offline(
records,
meta_data,
excludeMissingForms = TRUE,
fixed_fields = REDCAP_SYSTEM_FIELDS
)
A redcapConnection object.
logical(1) If all of the fields in a form are missing, would
you like to assume that they are purposefully missing? For instance, if
a patient did not experience an adverse event, the adverse event form would
contain no data and you would not want it in this report.
Additional arguments to pass to other methods. Currently ignored.
character A vector of field names that will be used as
the identifying fields in the output summary. This always includes the record
identifier (ie, the first field in the data dictionary). By default it
also includes any fields identified in REDCAP_SYSTEM_FIELDS, which
are fields that REDCap adds to exports to identify arms, events, etc..
named list with arguments to pass to exportRecords.
This allows for testing specific forms, events, and/or records. Internally, any
setting you make for factors, labels, dates, survey, or dag
arguments will be ignored.
An option for how to handle errors returned by the API.
see redcap_error
list Additional configuration parameters to pass to
POST. These are appended to any parameters in
rcon$config.
list Additional API parameters to pass into the
body of the API call. This provides users to execute calls with options
that may not otherwise be supported by redcapAPI.
character(1) A filename pointing to the raw records download from REDCap.
character(1) A filename pointing to the data dictionary download from REDCap.
Benjamin Nutter
The intention of this function is to generate a list of subject events that are missing and could potentially be values that should have been entered.
The branching logic from the data dictionary is parsed and translated into
and R expression. When a field with branching logic passes the logical
statement, it is evaluated with is.na, otherwise, it is set to
FALSE (non-missing, because there was never an opportunity to
provide a value). The utility of this function is limited to simple
logic where all of the
data exist within the same row. Any complex statements using events
will result in a failure.
Optionally, forms that are entirely missing can be determined to be non-missing. This is applicable when, for instance, a patient did not have an adverse event. In this case, a form dedicated to adverse events would contain meaningless missing values and could be excluded from the report.