The effect of missing data and imputation on the detection of bias in cognitive testing using differential item functioning methods.

ABSTRACT:

Background

Item response theory (IRT) methods for addressing differential item functioning (DIF) can detect group differences in responses to individual items (e.g., bias). IRT and DIF-detection methods have been used increasingly often to identify bias in cognitive test performance by characteristics (DIF grouping variables) such as hearing impairment, race, and educational attainment. Previous analyses have not considered the effect of missing data on inferences, although levels of missing cognitive data can be substantial in epidemiologic studies.

Methods

We used data from Visit 6 (2016-2017) of the Atherosclerosis Risk in Communities Neurocognitive Study (N = 3,580) to explicate the effect of artificially imposed missing data patterns and imputation on DIF detection.

SUBMITTER: Nichols E 

PROVIDER: S-EPMC8961895 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature