com_unit_missingness {dataquieR}

Counts all individuals with no measurements at all

Description

This implementation examines a crude version of unit missingness or unit-nonresponse (Kalton and Kasprzyk 1986), i.e. if all measurement variables in the study data are missing for an observation it has unit missingness.

The function can be applied on stratified data. In this case strata_vars must be specified.

Descriptor

Usage

com_unit_missingness(
  study_data,
  meta_data,
  id_vars = NULL,
  strata_vars = NULL,
  label_col
)

Arguments

study_data

data.frame the data frame that contains the measurements

meta_data

data.frame the data frame that contains metadata attributes of study data

id_vars

variable list optional, a (vectorized) call of ID-variables that should not be considered in the calculation of unit- missingness

strata_vars

variable optional, a string or integer variable used for stratification

label_col

variable attribute the name of the column in the metadata with labels of variables

Details

This implementations calculates a crude rate of unit-missingness. This type of missingness may have several causes and is an important research outcome. For example, unit-nonresponse may be selective regarding the targeted study population or technical reasons such as record-linkage may cause unit-missingness.

It has to be discriminated form segment and item missingness, since different causes and mechanisms may be the reason for unit-missingness.

Hint

This function does not support a resp_vars argument but id_vars, which have a roughly inverse logic behind: id_vars with values do not prevent a row from being considered missing, because an ID is the only hint for a unit that elsewise would not occur in the data at all.

List function.

Value

A list with:

• FlaggedStudyData: data.frame with id-only-rows flagged in a column Unit_missing

• SummaryData: data.frame with numbers and percentages of unit missingness

See Also

Online Documentation