Loading Tree…

DQI-2003

Definition

The proportion of eligible individuals who refuse to provide the information sought.

Explanation

Ideally, all targeted individuals should take part in the entire study. At any level of a study (e.g. the entire study, a follow up examination, an examination segment, or single items) some refusal may take place. Implementations related to this indicator target refusals at any of these levels. These are expressed as the proportion of all refusers out of the eligible subjects.

Example

In a cohort study, the target sample comprises 1000 adults with their primary place of residence in a defined region. All subjects have been selected based on population registries. All members of the target sample receive postal invitations. In case of no response contact attempts are made via phone or house visits. Because of the applied mailing method, it is reliably known, that mailings are returned, should the recipient have moved. In the latter case, a new address is provided, if known. Oriented at American Association for Public Opinion Research survey definitions (AAPOR, 2016 edition), a typical computation is:

Participants

  • I, P: Complete or partially complete examination (N=600)

  • R: Refusal (e.g. target participant declines to take part) and break-offs (an initiated examination is ended at an early stage) (N=100)

  • NC: Non-contacts (e.g. target participant with known eligibility unavailable) (N=40)

  • O: Other eligible no-responder (e.g. is unavailable at projected examination dates, examination data projected but examination not yet conducted) (N=110)

Unknown eligibility, no examination

  • NE: Not eligible (e.g. Persons deceased before the sampling date and persons living outside the sampling region do not belong to the target sample, duplicate listings) (N=150)

In total, 100 out of 850 eligible adults refuse participation, leading to a refusal-rate of 12%.

There is no corresponding indicator within the crude missingness domain.

Guidance

A refusal rate only applies to observational units with the possibility to refuse the provision of information.

In case of uncertainties about eligibility, AAPOR suggests to assume that a certain proportion of all observational units with unknown eligibility is not-eligible and should be removed from the denominator.

A high refusal rate is of particular relevance with regards to potential selection bias, because data values are commonly not missing randomly due to refusals from a sample.

Interpretation

The higher the refusal-rate, the lower the data quality.

Implementations

Literature

The International Statistical Institute, “The Oxford Dictionary of Statistical Terms”, edited by Yadolah Dodge, Oxford University Press, 2003.