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DQI-4006

Definition

Observed proportions differ from expected proportions.

Explanation

This indicator is used for categorical variables to assess discrepancies between observed and expected proportions.

Example

In an adult European general population, the percentage of persons with diabetes is expected to lie around 10%. Yet, the observed percentage is 89%. An inspection of the variable shows that the categories “diabetes” and “no diabetes” have been swaped.

Guidance

Checks for unexpected proportions of categorical variables should be conducted in any study.

Deviations of observed from expected proportions may indicate a wide range of issues such as examiner effects, device effects but also sampling issues.

In a designed study, little effects of study design factors, such as devices or examiners, should be exerted on proportions. Finding associations of relevance between these factors and sccale parameters are commonly indicative of measurement error.

For any interpretation it is important to take the number of cases into account. Low numbers may introduce a considerable amount of uncertainty.

Descriptors

Literature

  • Nonnemacher M, Nasseh D, Stausberg J. Datenqualität in der medizinischen Forschung: Leitlinie zum Adaptiven Datenmanagement in Kohortenstudien und Registern. Berlin: TMF e.V..; 2014.

  • Stausberg J, Bauer U, Nasseh D, et al. Indicators of data quality: review and requirements from the perspective of networked medical research MIBE 2019;15(1):1-8.